Overview

Dataset statistics

Number of variables88
Number of observations29634
Missing cells146412
Missing cells (%)5.6%
Total size in memory20.1 MiB
Average record size in memory712.0 B

Variable types

Numeric75
Text11
Unsupported2

Alerts

vlan_id has constant value ""Constant
tunnel_id has constant value ""Constant
bidirectional_cwr_packets has constant value ""Constant
bidirectional_ece_packets has constant value ""Constant
bidirectional_urg_packets has constant value ""Constant
src2dst_cwr_packets has constant value ""Constant
src2dst_ece_packets has constant value ""Constant
src2dst_urg_packets has constant value ""Constant
dst2src_cwr_packets has constant value ""Constant
dst2src_ece_packets has constant value ""Constant
dst2src_urg_packets has constant value ""Constant
label has constant value ""Constant
requested_server_name has 29634 (100.0%) missing valuesMissing
client_fingerprint has 29634 (100.0%) missing valuesMissing
server_fingerprint has 29114 (98.2%) missing valuesMissing
user_agent has 29627 (> 99.9%) missing valuesMissing
content_type has 28403 (95.8%) missing valuesMissing
expiration_id is highly skewed (γ1 = 20.35742216)Skewed
bidirectional_packets is highly skewed (γ1 = 93.18849779)Skewed
bidirectional_bytes is highly skewed (γ1 = 103.4685168)Skewed
src2dst_packets is highly skewed (γ1 = 107.2868794)Skewed
src2dst_bytes is highly skewed (γ1 = 113.0074403)Skewed
dst2src_packets is highly skewed (γ1 = 77.4217371)Skewed
dst2src_bytes is highly skewed (γ1 = 109.3421637)Skewed
bidirectional_min_piat_ms is highly skewed (γ1 = 34.06813685)Skewed
src2dst_min_piat_ms is highly skewed (γ1 = 21.58656427)Skewed
bidirectional_ack_packets is highly skewed (γ1 = 119.6243878)Skewed
bidirectional_psh_packets is highly skewed (γ1 = 151.3711071)Skewed
src2dst_ack_packets is highly skewed (γ1 = 128.000122)Skewed
src2dst_psh_packets is highly skewed (γ1 = 101.3922025)Skewed
dst2src_ack_packets is highly skewed (γ1 = 100.2871145)Skewed
dst2src_psh_packets is highly skewed (γ1 = 161.1968137)Skewed
requested_server_name is an unsupported type, check if it needs cleaning or further analysisUnsupported
client_fingerprint is an unsupported type, check if it needs cleaning or further analysisUnsupported
expiration_id has 29563 (99.8%) zerosZeros
src_port has 402 (1.4%) zerosZeros
dst_port has 402 (1.4%) zerosZeros
vlan_id has 29634 (100.0%) zerosZeros
tunnel_id has 29634 (100.0%) zerosZeros
bidirectional_duration_ms has 1339 (4.5%) zerosZeros
src2dst_duration_ms has 2645 (8.9%) zerosZeros
dst2src_first_seen_ms has 2434 (8.2%) zerosZeros
dst2src_last_seen_ms has 2434 (8.2%) zerosZeros
dst2src_duration_ms has 4874 (16.4%) zerosZeros
dst2src_packets has 2434 (8.2%) zerosZeros
dst2src_bytes has 2434 (8.2%) zerosZeros
bidirectional_stddev_ps has 2275 (7.7%) zerosZeros
src2dst_stddev_ps has 3734 (12.6%) zerosZeros
dst2src_min_ps has 2434 (8.2%) zerosZeros
dst2src_mean_ps has 2434 (8.2%) zerosZeros
dst2src_stddev_ps has 5799 (19.6%) zerosZeros
dst2src_max_ps has 2434 (8.2%) zerosZeros
bidirectional_min_piat_ms has 14222 (48.0%) zerosZeros
bidirectional_mean_piat_ms has 1339 (4.5%) zerosZeros
bidirectional_stddev_piat_ms has 2808 (9.5%) zerosZeros
bidirectional_max_piat_ms has 1339 (4.5%) zerosZeros
src2dst_min_piat_ms has 4337 (14.6%) zerosZeros
src2dst_mean_piat_ms has 2645 (8.9%) zerosZeros
src2dst_stddev_piat_ms has 4274 (14.4%) zerosZeros
src2dst_max_piat_ms has 2645 (8.9%) zerosZeros
dst2src_min_piat_ms has 7207 (24.3%) zerosZeros
dst2src_mean_piat_ms has 4874 (16.4%) zerosZeros
dst2src_stddev_piat_ms has 12142 (41.0%) zerosZeros
dst2src_max_piat_ms has 4874 (16.4%) zerosZeros
bidirectional_syn_packets has 3026 (10.2%) zerosZeros
bidirectional_cwr_packets has 29634 (100.0%) zerosZeros
bidirectional_ece_packets has 29634 (100.0%) zerosZeros
bidirectional_urg_packets has 29634 (100.0%) zerosZeros
bidirectional_ack_packets has 3488 (11.8%) zerosZeros
bidirectional_psh_packets has 27339 (92.3%) zerosZeros
bidirectional_rst_packets has 27268 (92.0%) zerosZeros
bidirectional_fin_packets has 4966 (16.8%) zerosZeros
src2dst_syn_packets has 3026 (10.2%) zerosZeros
src2dst_cwr_packets has 29634 (100.0%) zerosZeros
src2dst_ece_packets has 29634 (100.0%) zerosZeros
src2dst_urg_packets has 29634 (100.0%) zerosZeros
src2dst_ack_packets has 4817 (16.3%) zerosZeros
src2dst_psh_packets has 27969 (94.4%) zerosZeros
src2dst_rst_packets has 28405 (95.9%) zerosZeros
src2dst_fin_packets has 5579 (18.8%) zerosZeros
dst2src_syn_packets has 5117 (17.3%) zerosZeros
dst2src_cwr_packets has 29634 (100.0%) zerosZeros
dst2src_ece_packets has 29634 (100.0%) zerosZeros
dst2src_urg_packets has 29634 (100.0%) zerosZeros
dst2src_ack_packets has 3536 (11.9%) zerosZeros
dst2src_psh_packets has 27650 (93.3%) zerosZeros
dst2src_rst_packets has 28474 (96.1%) zerosZeros
dst2src_fin_packets has 5223 (17.6%) zerosZeros
application_is_guessed has 5251 (17.7%) zerosZeros
application_confidence has 318 (1.1%) zerosZeros
label has 29634 (100.0%) zerosZeros

Reproduction

Analysis started2023-06-15 15:30:02.774811
Analysis finished2023-06-15 15:30:05.521434
Duration2.75 seconds
Software versionydata-profiling vv4.2.0
Download configurationconfig.json

Variables

Unnamed: 0
Real number (ℝ)

Distinct23539
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24741.19525
Minimum0
Maximum74295
Zeros15
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:05.780347image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile962
Q16432.25
median19123
Q340262.5
95-th percentile65173.7
Maximum74295
Range74295
Interquartile range (IQR)33830.25

Descriptive statistics

Standard deviation21085.03277
Coefficient of variation (CV)0.8522236925
Kurtosis-0.7574698002
Mean24741.19525
Median Absolute Deviation (MAD)14927
Skewness0.6723490176
Sum733180580
Variance444578606.9
MonotonicityNot monotonic
2023-06-15T12:30:06.206185image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
0.1%
4 14
 
< 0.1%
1 14
 
< 0.1%
2 13
 
< 0.1%
5 13
 
< 0.1%
2542 6
 
< 0.1%
7 5
 
< 0.1%
2375 5
 
< 0.1%
2078 5
 
< 0.1%
1054 5
 
< 0.1%
Other values (23529) 29539
99.7%
ValueCountFrequency (%)
0 15
0.1%
1 14
< 0.1%
2 13
< 0.1%
3 2
 
< 0.1%
4 14
< 0.1%
ValueCountFrequency (%)
74295 1
< 0.1%
74275 1
< 0.1%
74054 1
< 0.1%
74048 1
< 0.1%
74041 1
< 0.1%

id
Real number (ℝ)

Distinct23539
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24741.19525
Minimum0
Maximum74295
Zeros15
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:06.782338image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile962
Q16432.25
median19123
Q340262.5
95-th percentile65173.7
Maximum74295
Range74295
Interquartile range (IQR)33830.25

Descriptive statistics

Standard deviation21085.03277
Coefficient of variation (CV)0.8522236925
Kurtosis-0.7574698002
Mean24741.19525
Median Absolute Deviation (MAD)14927
Skewness0.6723490176
Sum733180580
Variance444578606.9
MonotonicityNot monotonic
2023-06-15T12:30:07.314827image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
0.1%
4 14
 
< 0.1%
1 14
 
< 0.1%
2 13
 
< 0.1%
5 13
 
< 0.1%
2542 6
 
< 0.1%
7 5
 
< 0.1%
2375 5
 
< 0.1%
2078 5
 
< 0.1%
1054 5
 
< 0.1%
Other values (23529) 29539
99.7%
ValueCountFrequency (%)
0 15
0.1%
1 14
< 0.1%
2 13
< 0.1%
3 2
 
< 0.1%
4 14
< 0.1%
ValueCountFrequency (%)
74295 1
< 0.1%
74275 1
< 0.1%
74054 1
< 0.1%
74048 1
< 0.1%
74041 1
< 0.1%

expiration_id
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.002395896605
Minimum0
Maximum1
Zeros29563
Zeros (%)99.8%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:07.768944image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04889004953
Coefficient of variation (CV)20.40574265
Kurtosis412.4524736
Mean0.002395896605
Median Absolute Deviation (MAD)0
Skewness20.35742216
Sum71
Variance0.002390236943
MonotonicityNot monotonic
2023-06-15T12:30:08.192937image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 29563
99.8%
1 71
 
0.2%
ValueCountFrequency (%)
0 29563
99.8%
1 71
 
0.2%
ValueCountFrequency (%)
1 71
 
0.2%
0 29563
99.8%

src_ip
Text

Distinct559
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:08.803829image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length9
Mean length10.84018357
Min length2

Characters and Unicode

Total characters321238
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)0.8%

Sample

1st rowfe80::69dd:e614:2b2:dfd0
2nd row::
3rd rowfe80::69dd:e614:2b2:dfd0
4th row10.0.2.2
5th rowfe80::69dd:e614:2b2:dfd0
ValueCountFrequency (%)
10.0.2.15 14172
47.8%
192.168.1.191 10995
37.1%
10.0.0.46 2764
 
9.3%
fe80::69dd:e614:2b2:dfd0 319
 
1.1%
24
 
0.1%
172.217.23.228 23
 
0.1%
78.26.20.251 20
 
0.1%
fe80::fc66:5abf:d63a:94fb 19
 
0.1%
216.58.201.98 16
 
0.1%
152.163.66.165 15
 
0.1%
Other values (549) 1267
 
4.3%
2023-06-15T12:30:09.925530image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 89590
27.9%
. 87735
27.3%
0 38237
11.9%
2 28381
 
8.8%
9 23143
 
7.2%
5 15340
 
4.8%
6 15332
 
4.8%
8 12101
 
3.8%
4 4052
 
1.3%
: 1872
 
0.6%
Other values (8) 5455
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 228291
71.1%
Other Punctuation 89607
 
27.9%
Lowercase Letter 3340
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 89590
39.2%
0 38237
16.7%
2 28381
 
12.4%
9 23143
 
10.1%
5 15340
 
6.7%
6 15332
 
6.7%
8 12101
 
5.3%
4 4052
 
1.8%
3 1180
 
0.5%
7 935
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
d 1348
40.4%
f 784
23.5%
e 715
21.4%
b 372
 
11.1%
a 85
 
2.5%
c 36
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 87735
97.9%
: 1872
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 317898
99.0%
Latin 3340
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 89590
28.2%
. 87735
27.6%
0 38237
12.0%
2 28381
 
8.9%
9 23143
 
7.3%
5 15340
 
4.8%
6 15332
 
4.8%
8 12101
 
3.8%
4 4052
 
1.3%
: 1872
 
0.6%
Other values (2) 2115
 
0.7%
Latin
ValueCountFrequency (%)
d 1348
40.4%
f 784
23.5%
e 715
21.4%
b 372
 
11.1%
a 85
 
2.5%
c 36
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 321238
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 89590
27.9%
. 87735
27.3%
0 38237
11.9%
2 28381
 
8.8%
9 23143
 
7.2%
5 15340
 
4.8%
6 15332
 
4.8%
8 12101
 
3.8%
4 4052
 
1.3%
: 1872
 
0.6%
Other values (8) 5455
 
1.7%
Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:10.335914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters503778
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row08:00:27:a3:83:43
2nd row08:00:27:a3:83:43
3rd row08:00:27:a3:83:43
4th row52:54:00:12:35:02
5th row08:00:27:a3:83:43
ValueCountFrequency (%)
08:00:27:a3:83:43 14502
48.9%
60:6c:66:cb:78:61 10995
37.1%
78:e4:00:6c:39:cd 2764
 
9.3%
00:13:33:b0:18:50 1044
 
3.5%
38:72:c0:5e:6b:22 218
 
0.7%
52:54:00:12:35:02 30
 
0.1%
d0:53:49:1b:0c:90 23
 
0.1%
44:6d:57:7c:fb:74 20
 
0.1%
10:a5:d0:3d:d4:a7 15
 
0.1%
2c:6e:85:56:dd:b7 7
 
< 0.1%
Other values (5) 16
 
0.1%
2023-06-15T12:30:11.063323image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 148170
29.4%
0 64647
12.8%
6 57995
 
11.5%
3 49697
 
9.9%
8 44052
 
8.7%
7 28576
 
5.7%
c 27794
 
5.5%
4 17421
 
3.5%
2 15259
 
3.0%
a 14540
 
2.9%
Other values (7) 35627
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 295051
58.6%
Other Punctuation 148170
29.4%
Lowercase Letter 60557
 
12.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 64647
21.9%
6 57995
19.7%
3 49697
16.8%
8 44052
14.9%
7 28576
9.7%
4 17421
 
5.9%
2 15259
 
5.2%
1 13161
 
4.5%
9 2815
 
1.0%
5 1428
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
c 27794
45.9%
a 14540
24.0%
b 12318
20.3%
e 2998
 
5.0%
d 2883
 
4.8%
f 24
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
: 148170
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 443221
88.0%
Latin 60557
 
12.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 148170
33.4%
0 64647
14.6%
6 57995
 
13.1%
3 49697
 
11.2%
8 44052
 
9.9%
7 28576
 
6.4%
4 17421
 
3.9%
2 15259
 
3.4%
1 13161
 
3.0%
9 2815
 
0.6%
Latin
ValueCountFrequency (%)
c 27794
45.9%
a 14540
24.0%
b 12318
20.3%
e 2998
 
5.0%
d 2883
 
4.8%
f 24
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 503778
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 148170
29.4%
0 64647
12.8%
6 57995
 
11.5%
3 49697
 
9.9%
8 44052
 
8.7%
7 28576
 
5.7%
c 27794
 
5.5%
4 17421
 
3.5%
2 15259
 
3.0%
a 14540
 
2.9%
Other values (7) 35627
 
7.1%
Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:11.344735image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters237072
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row08:00:27
2nd row08:00:27
3rd row08:00:27
4th row52:54:00
5th row08:00:27
ValueCountFrequency (%)
08:00:27 14504
48.9%
60:6c:66 10995
37.1%
78:e4:00 2764
 
9.3%
00:13:33 1044
 
3.5%
38:72:c0 218
 
0.7%
52:54:00 30
 
0.1%
d0:53:49 23
 
0.1%
44:6d:57 20
 
0.1%
10:a5:d0 15
 
0.1%
2c:6e:85 7
 
< 0.1%
Other values (4) 14
 
< 0.1%
2023-06-15T12:30:12.080283image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 62460
26.3%
: 59268
25.0%
6 44011
18.6%
7 17510
 
7.4%
8 17509
 
7.4%
2 14759
 
6.2%
c 11228
 
4.7%
3 3378
 
1.4%
4 2866
 
1.2%
e 2771
 
1.2%
Other values (6) 1312
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 163713
69.1%
Other Punctuation 59268
 
25.0%
Lowercase Letter 14091
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 62460
38.2%
6 44011
26.9%
7 17510
 
10.7%
8 17509
 
10.7%
2 14759
 
9.0%
3 3378
 
2.1%
4 2866
 
1.8%
1 1063
 
0.6%
5 129
 
0.1%
9 28
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
c 11228
79.7%
e 2771
 
19.7%
d 66
 
0.5%
a 21
 
0.1%
b 5
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
: 59268
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 222981
94.1%
Latin 14091
 
5.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 62460
28.0%
: 59268
26.6%
6 44011
19.7%
7 17510
 
7.9%
8 17509
 
7.9%
2 14759
 
6.6%
3 3378
 
1.5%
4 2866
 
1.3%
1 1063
 
0.5%
5 129
 
0.1%
Latin
ValueCountFrequency (%)
c 11228
79.7%
e 2771
 
19.7%
d 66
 
0.5%
a 21
 
0.1%
b 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 237072
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 62460
26.3%
: 59268
25.0%
6 44011
18.6%
7 17510
 
7.4%
8 17509
 
7.4%
2 14759
 
6.2%
c 11228
 
4.7%
3 3378
 
1.4%
4 2866
 
1.2%
e 2771
 
1.2%
Other values (6) 1312
 
0.6%

src_port
Real number (ℝ)

Distinct15005
Distinct (%)50.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49240.30101
Minimum0
Maximum65533
Zeros402
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:12.423764image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile443
Q146340
median53089
Q358606
95-th percentile61095.05
Maximum65533
Range65533
Interquartile range (IQR)12266

Descriptive statistics

Standard deviation14545.6101
Coefficient of variation (CV)0.2954005115
Kurtosis5.066250774
Mean49240.30101
Median Absolute Deviation (MAD)5716
Skewness-2.267021213
Sum1459187080
Variance211574773.2
MonotonicityNot monotonic
2023-06-15T12:30:12.740348image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59370 2091
 
7.1%
80 889
 
3.0%
0 402
 
1.4%
546 304
 
1.0%
443 178
 
0.6%
49210 15
 
0.1%
67 14
 
< 0.1%
123 12
 
< 0.1%
58104 10
 
< 0.1%
58134 9
 
< 0.1%
Other values (14995) 25710
86.8%
ValueCountFrequency (%)
0 402
1.4%
67 14
 
< 0.1%
80 889
3.0%
123 12
 
< 0.1%
137 1
 
< 0.1%
ValueCountFrequency (%)
65533 1
< 0.1%
65531 2
< 0.1%
65525 1
< 0.1%
65524 1
< 0.1%
65521 2
< 0.1%

dst_ip
Text

Distinct5379
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:13.306130image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length35
Median length25
Mean length12.86930553
Min length7

Characters and Unicode

Total characters381369
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1866 ?
Unique (%)6.3%

Sample

1st rowff02::16
2nd rowff02::1:ffb2:dfd0
3rd rowff02::2
4th row10.0.2.15
5th rowff02::1:2
ValueCountFrequency (%)
23.51.123.27 1785
 
6.0%
192.168.1.191 1042
 
3.5%
93.184.220.29 761
 
2.6%
178.255.83.1 586
 
2.0%
ff02::1:2 304
 
1.0%
188.121.36.239 299
 
1.0%
172.217.23.238 295
 
1.0%
173.241.240.220 228
 
0.8%
172.217.23.227 224
 
0.8%
172.217.23.226 221
 
0.7%
Other values (5369) 23889
80.6%
2023-06-15T12:30:14.086833image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 87735
23.0%
1 70417
18.5%
2 57554
15.1%
3 26983
 
7.1%
5 23522
 
6.2%
4 20727
 
5.4%
7 20615
 
5.4%
9 19084
 
5.0%
0 18509
 
4.9%
6 17256
 
4.5%
Other values (8) 18967
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 291568
76.5%
Other Punctuation 88879
 
23.3%
Lowercase Letter 922
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 70417
24.2%
2 57554
19.7%
3 26983
 
9.3%
5 23522
 
8.1%
4 20727
 
7.1%
7 20615
 
7.1%
9 19084
 
6.5%
0 18509
 
6.3%
6 17256
 
5.9%
8 16901
 
5.8%
Lowercase Letter
ValueCountFrequency (%)
f 827
89.7%
d 41
 
4.4%
b 26
 
2.8%
a 18
 
2.0%
e 6
 
0.7%
c 4
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 87735
98.7%
: 1144
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 380447
99.8%
Latin 922
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 87735
23.1%
1 70417
18.5%
2 57554
15.1%
3 26983
 
7.1%
5 23522
 
6.2%
4 20727
 
5.4%
7 20615
 
5.4%
9 19084
 
5.0%
0 18509
 
4.9%
6 17256
 
4.5%
Other values (2) 18045
 
4.7%
Latin
ValueCountFrequency (%)
f 827
89.7%
d 41
 
4.4%
b 26
 
2.8%
a 18
 
2.0%
e 6
 
0.7%
c 4
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 381369
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 87735
23.0%
1 70417
18.5%
2 57554
15.1%
3 26983
 
7.1%
5 23522
 
6.2%
4 20727
 
5.4%
7 20615
 
5.4%
9 19084
 
5.0%
0 18509
 
4.9%
6 17256
 
4.5%
Other values (8) 18967
 
5.0%
Distinct19
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:14.481176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters503778
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row33:33:00:00:00:16
2nd row33:33:ff:b2:df:d0
3rd row33:33:00:00:00:02
4th row08:00:27:a3:83:43
5th row33:33:00:01:00:02
ValueCountFrequency (%)
52:54:00:12:35:02 14161
47.8%
00:13:33:b0:18:50 10995
37.1%
38:72:c0:5e:6b:22 2762
 
9.3%
60:6c:66:cb:78:61 1042
 
3.5%
33:33:00:01:00:02 304
 
1.0%
78:e4:00:6c:39:cd 219
 
0.7%
33:33:00:00:00:16 36
 
0.1%
08:00:27:a3:83:43 30
 
0.1%
01:00:5e:00:00:16 19
 
0.1%
33:33:00:00:00:02 17
 
0.1%
Other values (9) 49
 
0.2%
2023-06-15T12:30:15.254164image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 148170
29.4%
0 93250
18.5%
5 56271
 
11.2%
3 51773
 
10.3%
2 51139
 
10.2%
1 37600
 
7.5%
8 15094
 
3.0%
b 14819
 
2.9%
4 14416
 
2.9%
6 8250
 
1.6%
Other values (7) 12996
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 332074
65.9%
Other Punctuation 148170
29.4%
Lowercase Letter 23534
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 93250
28.1%
5 56271
16.9%
3 51773
15.6%
2 51139
15.4%
1 37600
11.3%
8 15094
 
4.5%
4 14416
 
4.3%
6 8250
 
2.5%
7 4058
 
1.2%
9 223
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
b 14819
63.0%
c 5298
 
22.5%
e 3018
 
12.8%
d 258
 
1.1%
f 95
 
0.4%
a 46
 
0.2%
Other Punctuation
ValueCountFrequency (%)
: 148170
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 480244
95.3%
Latin 23534
 
4.7%

Most frequent character per script

Common
ValueCountFrequency (%)
: 148170
30.9%
0 93250
19.4%
5 56271
 
11.7%
3 51773
 
10.8%
2 51139
 
10.6%
1 37600
 
7.8%
8 15094
 
3.1%
4 14416
 
3.0%
6 8250
 
1.7%
7 4058
 
0.8%
Latin
ValueCountFrequency (%)
b 14819
63.0%
c 5298
 
22.5%
e 3018
 
12.8%
d 258
 
1.1%
f 95
 
0.4%
a 46
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 503778
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 148170
29.4%
0 93250
18.5%
5 56271
 
11.2%
3 51773
 
10.3%
2 51139
 
10.2%
1 37600
 
7.5%
8 15094
 
3.0%
b 14819
 
2.9%
4 14416
 
2.9%
6 8250
 
1.6%
Other values (7) 12996
 
2.6%
Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:15.884694image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters237072
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row33:33:00
2nd row33:33:ff
3rd row33:33:00
4th row08:00:27
5th row33:33:00
ValueCountFrequency (%)
52:54:00 14161
47.8%
00:13:33 10995
37.1%
38:72:c0 2762
 
9.3%
60:6c:66 1042
 
3.5%
33:33:00 367
 
1.2%
78:e4:00 219
 
0.7%
08:00:27 34
 
0.1%
01:00:5e 29
 
0.1%
33:33:ff 18
 
0.1%
ff:ff:ff 3
 
< 0.1%
Other values (2) 4
 
< 0.1%
2023-06-15T12:30:16.856609image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 59268
25.0%
0 55483
23.4%
3 37287
15.7%
5 28353
12.0%
2 16957
 
7.2%
4 14380
 
6.1%
1 11026
 
4.7%
6 4172
 
1.8%
c 3806
 
1.6%
8 3017
 
1.3%
Other values (5) 3323
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 173692
73.3%
Other Punctuation 59268
 
25.0%
Lowercase Letter 4112
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 55483
31.9%
3 37287
21.5%
5 28353
16.3%
2 16957
 
9.8%
4 14380
 
8.3%
1 11026
 
6.3%
6 4172
 
2.4%
8 3017
 
1.7%
7 3015
 
1.7%
9 2
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
c 3806
92.6%
e 248
 
6.0%
f 56
 
1.4%
b 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
: 59268
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 232960
98.3%
Latin 4112
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
: 59268
25.4%
0 55483
23.8%
3 37287
16.0%
5 28353
12.2%
2 16957
 
7.3%
4 14380
 
6.2%
1 11026
 
4.7%
6 4172
 
1.8%
8 3017
 
1.3%
7 3015
 
1.3%
Latin
ValueCountFrequency (%)
c 3806
92.6%
e 248
 
6.0%
f 56
 
1.4%
b 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 237072
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 59268
25.0%
0 55483
23.4%
3 37287
15.7%
5 28353
12.0%
2 16957
 
7.2%
4 14380
 
6.1%
1 11026
 
4.7%
6 4172
 
1.8%
c 3806
 
1.6%
8 3017
 
1.3%
Other values (5) 3323
 
1.4%

dst_port
Real number (ℝ)

Distinct1857
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4882.748903
Minimum0
Maximum65502
Zeros402
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:17.400429image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile80
Q180
median80
Q380
95-th percentile46540
Maximum65502
Range65502
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13840.04135
Coefficient of variation (CV)2.834477386
Kurtosis6.8612227
Mean4882.748903
Median Absolute Deviation (MAD)0
Skewness2.868853263
Sum144695381
Variance191546744.5
MonotonicityNot monotonic
2023-06-15T12:30:17.891642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 23408
79.0%
443 1595
 
5.4%
0 402
 
1.4%
547 304
 
1.0%
54081 178
 
0.6%
6881 142
 
0.5%
51413 138
 
0.5%
51666 53
 
0.2%
40000 44
 
0.1%
25407 40
 
0.1%
Other values (1847) 3330
 
11.2%
ValueCountFrequency (%)
0 402
 
1.4%
7 1
 
< 0.1%
22 1
 
< 0.1%
68 14
 
< 0.1%
80 23408
79.0%
ValueCountFrequency (%)
65502 1
< 0.1%
65173 2
< 0.1%
65035 2
< 0.1%
64964 2
< 0.1%
64913 2
< 0.1%

protocol
Real number (ℝ)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.990517649
Minimum1
Maximum58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:18.383845image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q16
median6
Q36
95-th percentile17
Maximum58
Range57
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.013931193
Coefficient of variation (CV)0.5741965609
Kurtosis65.41799707
Mean6.990517649
Median Absolute Deviation (MAD)0
Skewness6.3664766
Sum207157
Variance16.11164362
MonotonicityNot monotonic
2023-06-15T12:30:18.789269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
6 26766
90.3%
17 2466
 
8.3%
1 309
 
1.0%
58 74
 
0.2%
2 19
 
0.1%
ValueCountFrequency (%)
1 309
 
1.0%
2 19
 
0.1%
6 26766
90.3%
17 2466
 
8.3%
58 74
 
0.2%
ValueCountFrequency (%)
58 74
 
0.2%
17 2466
 
8.3%
6 26766
90.3%
2 19
 
0.1%
1 309
 
1.0%

ip_version
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.026253628
Minimum4
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:19.167364image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4
Q14
median4
Q34
95-th percentile4
Maximum6
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2276395196
Coefficient of variation (CV)0.05653879279
Kurtosis71.20546605
Mean4.026253628
Median Absolute Deviation (MAD)0
Skewness8.555738448
Sum119314
Variance0.05181975088
MonotonicityNot monotonic
2023-06-15T12:30:19.520321image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
4 29245
98.7%
6 389
 
1.3%
ValueCountFrequency (%)
4 29245
98.7%
6 389
 
1.3%
ValueCountFrequency (%)
6 389
 
1.3%
4 29245
98.7%

vlan_id
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros29634
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:19.813559image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-15T12:30:20.191719image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%

tunnel_id
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros29634
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:20.555663image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-15T12:30:20.842170image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
Distinct23345
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.502193272 × 1011
Minimum7392
Maximum1.493732834 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:21.860778image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum7392
5-th percentile910264.7
Q15761072.75
median1.387314804 × 1012
Q31.493729159 × 1012
95-th percentile1.493731773 × 1012
Maximum1.493732834 × 1012
Range1.493732827 × 1012
Interquartile range (IQR)1.493723398 × 1012

Descriptive statistics

Standard deviation7.368508013 × 1011
Coefficient of variation (CV)0.9821805098
Kurtosis-1.992927081
Mean7.502193272 × 1011
Median Absolute Deviation (MAD)1.064178079 × 1011
Skewness-0.0327642912
Sum2.223199954 × 1016
Variance5.429491034 × 1023
MonotonicityNot monotonic
2023-06-15T12:30:22.447798image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.49373175 × 101224
 
0.1%
1.493730733 × 101219
 
0.1%
1.49373175 × 101217
 
0.1%
1.493731161 × 101217
 
0.1%
1.493730732 × 101216
 
0.1%
1.493729182 × 101215
 
0.1%
1.493728079 × 101215
 
0.1%
1.493728993 × 101214
 
< 0.1%
1.493730733 × 101214
 
< 0.1%
1.493731052 × 101214
 
< 0.1%
Other values (23335) 29469
99.4%
ValueCountFrequency (%)
7392 1
< 0.1%
8122 1
< 0.1%
13159 1
< 0.1%
14160 1
< 0.1%
30507 1
< 0.1%
ValueCountFrequency (%)
1.493732834 × 10121
 
< 0.1%
1.493732834 × 10121
 
< 0.1%
1.493732824 × 10121
 
< 0.1%
1.493732824 × 10121
 
< 0.1%
1.493732824 × 10123
< 0.1%
Distinct24827
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.502193442 × 1011
Minimum14160
Maximum1.493732969 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:23.038883image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum14160
5-th percentile920260.45
Q15801669.75
median1.387314876 × 1012
Q31.493729161 × 1012
95-th percentile1.493731789 × 1012
Maximum1.493732969 × 1012
Range1.493732955 × 1012
Interquartile range (IQR)1.49372336 × 1012

Descriptive statistics

Standard deviation7.368507969 × 1011
Coefficient of variation (CV)0.9821804817
Kurtosis-1.992927083
Mean7.502193442 × 1011
Median Absolute Deviation (MAD)1.06417748 × 1011
Skewness-0.032764293
Sum2.223200005 × 1016
Variance5.429490969 × 1023
MonotonicityNot monotonic
2023-06-15T12:30:23.592315image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.493728087 × 101215
 
0.1%
1.493731028 × 101215
 
0.1%
1.493728071 × 101213
 
< 0.1%
1.493728072 × 101210
 
< 0.1%
1.493727074 × 101210
 
< 0.1%
1.493729276 × 10129
 
< 0.1%
1.493728071 × 10129
 
< 0.1%
1.493730788 × 10129
 
< 0.1%
1.387314964 × 10128
 
< 0.1%
1.49372792 × 10128
 
< 0.1%
Other values (24817) 29528
99.6%
ValueCountFrequency (%)
14160 1
< 0.1%
15161 1
< 0.1%
20650 1
< 0.1%
40491 1
< 0.1%
40991 1
< 0.1%
ValueCountFrequency (%)
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732897 × 10121
< 0.1%
1.493732894 × 10121
< 0.1%

bidirectional_duration_ms
Real number (ℝ)

Distinct11204
Distinct (%)37.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17015.32223
Minimum0
Maximum1799507
Zeros1339
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:24.104669image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile42
Q11471.25
median6004
Q37905.75
95-th percentile24806.4
Maximum1799507
Range1799507
Interquartile range (IQR)6434.5

Descriptive statistics

Standard deviation110032.8608
Coefficient of variation (CV)6.466692743
Kurtosis204.9605503
Mean17015.32223
Median Absolute Deviation (MAD)3039
Skewness13.87948922
Sum504232059
Variance1.210723045 × 1010
MonotonicityNot monotonic
2023-06-15T12:30:24.592047image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1339
 
4.5%
3002 35
 
0.1%
255 28
 
0.1%
88 20
 
0.1%
94 19
 
0.1%
42 19
 
0.1%
139 18
 
0.1%
46 18
 
0.1%
106 18
 
0.1%
5989 18
 
0.1%
Other values (11194) 28102
94.8%
ValueCountFrequency (%)
0 1339
4.5%
1 4
 
< 0.1%
5 2
 
< 0.1%
6 3
 
< 0.1%
11 2
 
< 0.1%
ValueCountFrequency (%)
1799507 1
< 0.1%
1798353 1
< 0.1%
1798350 1
< 0.1%
1798311 1
< 0.1%
1798299 1
< 0.1%

bidirectional_packets
Real number (ℝ)

Distinct268
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.2884862
Minimum1
Maximum392213
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:25.021028image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median7
Q37
95-th percentile16
Maximum392213
Range392212
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3064.488459
Coefficient of variation (CV)56.44822085
Kurtosis10235.20075
Mean54.2884862
Median Absolute Deviation (MAD)1
Skewness93.18849779
Sum1608785
Variance9391089.514
MonotonicityNot monotonic
2023-06-15T12:30:25.396748image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 13464
45.4%
6 6524
22.0%
2 1479
 
5.0%
1 1325
 
4.5%
3 1243
 
4.2%
8 1067
 
3.6%
5 930
 
3.1%
9 575
 
1.9%
4 564
 
1.9%
10 272
 
0.9%
Other values (258) 2191
 
7.4%
ValueCountFrequency (%)
1 1325
4.5%
2 1479
5.0%
3 1243
4.2%
4 564
 
1.9%
5 930
3.1%
ValueCountFrequency (%)
392213 1
< 0.1%
184518 2
< 0.1%
124890 2
< 0.1%
110611 2
< 0.1%
16236 2
< 0.1%

bidirectional_bytes
Real number (ℝ)

Distinct2176
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44046.87902
Minimum54
Maximum424668890
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:25.887310image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile143
Q1390
median394
Q3408
95-th percentile2970.1
Maximum424668890
Range424668836
Interquartile range (IQR)18

Descriptive statistics

Standard deviation3084514.7
Coefficient of variation (CV)70.02799673
Kurtosis12790.21927
Mean44046.87902
Median Absolute Deviation (MAD)14
Skewness103.4685168
Sum1305285213
Variance9.514230935 × 1012
MonotonicityNot monotonic
2023-06-15T12:30:26.345601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
394 6434
21.7%
408 6186
20.9%
390 5543
18.7%
143 952
 
3.2%
474 680
 
2.3%
452 548
 
1.8%
174 545
 
1.8%
460 536
 
1.8%
342 531
 
1.8%
128 353
 
1.2%
Other values (2166) 7326
24.7%
ValueCountFrequency (%)
54 5
 
< 0.1%
62 16
 
0.1%
66 2
 
< 0.1%
70 29
 
0.1%
74 114
0.4%
ValueCountFrequency (%)
424668890 1
< 0.1%
148005382 2
< 0.1%
128190733 2
< 0.1%
110825666 2
< 0.1%
13090548 2
< 0.1%

src2dst_first_seen_ms
Real number (ℝ)

Distinct23345
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.502193272 × 1011
Minimum7392
Maximum1.493732834 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:26.802753image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum7392
5-th percentile910264.7
Q15761072.75
median1.387314804 × 1012
Q31.493729159 × 1012
95-th percentile1.493731773 × 1012
Maximum1.493732834 × 1012
Range1.493732827 × 1012
Interquartile range (IQR)1.493723398 × 1012

Descriptive statistics

Standard deviation7.368508013 × 1011
Coefficient of variation (CV)0.9821805098
Kurtosis-1.992927081
Mean7.502193272 × 1011
Median Absolute Deviation (MAD)1.064178079 × 1011
Skewness-0.0327642912
Sum2.223199954 × 1016
Variance5.429491034 × 1023
MonotonicityNot monotonic
2023-06-15T12:30:27.211624image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.49373175 × 101224
 
0.1%
1.493730733 × 101219
 
0.1%
1.49373175 × 101217
 
0.1%
1.493731161 × 101217
 
0.1%
1.493730732 × 101216
 
0.1%
1.493729182 × 101215
 
0.1%
1.493728079 × 101215
 
0.1%
1.493728993 × 101214
 
< 0.1%
1.493730733 × 101214
 
< 0.1%
1.493731052 × 101214
 
< 0.1%
Other values (23335) 29469
99.4%
ValueCountFrequency (%)
7392 1
< 0.1%
8122 1
< 0.1%
13159 1
< 0.1%
14160 1
< 0.1%
30507 1
< 0.1%
ValueCountFrequency (%)
1.493732834 × 10121
 
< 0.1%
1.493732834 × 10121
 
< 0.1%
1.493732824 × 10121
 
< 0.1%
1.493732824 × 10121
 
< 0.1%
1.493732824 × 10123
< 0.1%

src2dst_last_seen_ms
Real number (ℝ)

Distinct24772
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.502193442 × 1011
Minimum14160
Maximum1.493732969 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:27.771591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum14160
5-th percentile920260.45
Q15801668.75
median1.387314876 × 1012
Q31.493729161 × 1012
95-th percentile1.493731789 × 1012
Maximum1.493732969 × 1012
Range1.493732955 × 1012
Interquartile range (IQR)1.49372336 × 1012

Descriptive statistics

Standard deviation7.368507969 × 1011
Coefficient of variation (CV)0.9821804817
Kurtosis-1.992927083
Mean7.502193442 × 1011
Median Absolute Deviation (MAD)1.064177484 × 1011
Skewness-0.032764293
Sum2.223200005 × 1016
Variance5.429490968 × 1023
MonotonicityNot monotonic
2023-06-15T12:30:28.234636image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.387315073 × 101216
 
0.1%
1.493731028 × 101215
 
0.1%
1.493728087 × 101214
 
< 0.1%
1.493727256 × 101213
 
< 0.1%
1.493727967 × 101211
 
< 0.1%
1.493727074 × 101210
 
< 0.1%
1.387315238 × 101210
 
< 0.1%
1.387315193 × 101210
 
< 0.1%
1.387314868 × 101210
 
< 0.1%
1.387315618 × 101210
 
< 0.1%
Other values (24762) 29515
99.6%
ValueCountFrequency (%)
14160 1
< 0.1%
15161 1
< 0.1%
20650 1
< 0.1%
40491 1
< 0.1%
40991 1
< 0.1%
ValueCountFrequency (%)
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732897 × 10121
< 0.1%
1.493732894 × 10121
< 0.1%

src2dst_duration_ms
Real number (ℝ)

Distinct11081
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16960.40335
Minimum0
Maximum1799507
Zeros2645
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:28.791089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11385.25
median5991
Q37856
95-th percentile24121.95
Maximum1799507
Range1799507
Interquartile range (IQR)6470.75

Descriptive statistics

Standard deviation110031.7161
Coefficient of variation (CV)6.487564819
Kurtosis204.9788809
Mean16960.40335
Median Absolute Deviation (MAD)3061.5
Skewness13.88034991
Sum502604593
Variance1.210697855 × 1010
MonotonicityNot monotonic
2023-06-15T12:30:29.343380image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2645
 
8.9%
3002 35
 
0.1%
255 28
 
0.1%
5989 18
 
0.1%
3001 17
 
0.1%
6028 17
 
0.1%
5870 16
 
0.1%
6037 16
 
0.1%
6038 15
 
0.1%
6156 15
 
0.1%
Other values (11071) 26812
90.5%
ValueCountFrequency (%)
0 2645
8.9%
1 4
 
< 0.1%
5 2
 
< 0.1%
6 3
 
< 0.1%
11 2
 
< 0.1%
ValueCountFrequency (%)
1799507 1
< 0.1%
1798351 1
< 0.1%
1798348 1
< 0.1%
1798309 1
< 0.1%
1798299 1
< 0.1%

src2dst_packets
Real number (ℝ)

Distinct188
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.85762975
Minimum1
Maximum271835
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:29.881907image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median4
Q34
95-th percentile8
Maximum271835
Range271834
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1950.126057
Coefficient of variation (CV)61.21378371
Kurtosis13495.46792
Mean31.85762975
Median Absolute Deviation (MAD)0
Skewness107.2868794
Sum944069
Variance3802991.639
MonotonicityNot monotonic
2023-06-15T12:30:30.422181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 19525
65.9%
1 2637
 
8.9%
2 1633
 
5.5%
3 1608
 
5.4%
5 1486
 
5.0%
7 572
 
1.9%
6 419
 
1.4%
8 281
 
0.9%
9 165
 
0.6%
10 157
 
0.5%
Other values (178) 1151
 
3.9%
ValueCountFrequency (%)
1 2637
 
8.9%
2 1633
 
5.5%
3 1608
 
5.4%
4 19525
65.9%
5 1486
 
5.0%
ValueCountFrequency (%)
271835 1
< 0.1%
97615 2
< 0.1%
91724 2
< 0.1%
36078 2
< 0.1%
9702 2
< 0.1%

src2dst_bytes
Real number (ℝ)

Distinct1511
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32634.70966
Minimum54
Maximum383809522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:30.954170image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile130.6
Q1224
median228
Q3272
95-th percentile1062.35
Maximum383809522
Range383809468
Interquartile range (IQR)48

Descriptive statistics

Standard deviation2694761.763
Coefficient of variation (CV)82.57348666
Kurtosis14661.71605
Mean32634.70966
Median Absolute Deviation (MAD)44
Skewness113.0074403
Sum967096986
Variance7.261740958 × 1012
MonotonicityNot monotonic
2023-06-15T12:30:31.485726image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
272 7326
24.7%
228 6436
21.7%
224 5543
18.7%
143 1828
 
6.2%
206 989
 
3.3%
338 621
 
2.1%
286 587
 
2.0%
116 545
 
1.8%
74 497
 
1.7%
136 389
 
1.3%
Other values (1501) 4873
16.4%
ValueCountFrequency (%)
54 8
 
< 0.1%
62 16
 
0.1%
66 2
 
< 0.1%
70 43
 
0.1%
74 497
1.7%
ValueCountFrequency (%)
383809522 1
< 0.1%
146054307 2
< 0.1%
111505374 2
< 0.1%
12644847 2
< 0.1%
5898809 1
< 0.1%

dst2src_first_seen_ms
Real number (ℝ)

Distinct22982
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.713960324 × 1011
Minimum0
Maximum1.493732856 × 1012
Zeros2434
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:32.041756image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13603465.5
median12225495.5
Q31.493729117 × 1012
95-th percentile1.49373177 × 1012
Maximum1.493732856 × 1012
Range1.493732856 × 1012
Interquartile range (IQR)1.493725513 × 1012

Descriptive statistics

Standard deviation7.377968593 × 1011
Coefficient of variation (CV)1.098899641
Kurtosis-1.960274683
Mean6.713960324 × 1011
Median Absolute Deviation (MAD)12225495.5
Skewness0.190727121
Sum1.989615002 × 1016
Variance5.443442056 × 1023
MonotonicityNot monotonic
2023-06-15T12:30:32.541643image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2434
 
8.2%
3793598 8
 
< 0.1%
338249 7
 
< 0.1%
1.493729117 × 10127
 
< 0.1%
1.493726611 × 10127
 
< 0.1%
1.493728803 × 10127
 
< 0.1%
1.493731477 × 10127
 
< 0.1%
1.493727914 × 10127
 
< 0.1%
1.493731752 × 10127
 
< 0.1%
1.493728182 × 10126
 
< 0.1%
Other values (22972) 27137
91.6%
ValueCountFrequency (%)
0 2434
8.2%
12401 1
 
< 0.1%
13159 1
 
< 0.1%
14160 1
 
< 0.1%
35521 1
 
< 0.1%
ValueCountFrequency (%)
1.493732856 × 10121
< 0.1%
1.493732837 × 10121
< 0.1%
1.493732834 × 10121
< 0.1%
1.493732834 × 10121
< 0.1%
1.493732824 × 10121
< 0.1%

dst2src_last_seen_ms
Real number (ℝ)

Distinct22262
Distinct (%)75.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.713960466 × 1011
Minimum0
Maximum1.493732969 × 1012
Zeros2434
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:33.069586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13616476
median12243059.5
Q31.493729122 × 1012
95-th percentile1.493731784 × 1012
Maximum1.493732969 × 1012
Range1.493732969 × 1012
Interquartile range (IQR)1.493725505 × 1012

Descriptive statistics

Standard deviation7.377968563 × 1011
Coefficient of variation (CV)1.098899614
Kurtosis-1.960274686
Mean6.713960466 × 1011
Median Absolute Deviation (MAD)12243059.5
Skewness0.1907271195
Sum1.989615044 × 1016
Variance5.443442012 × 1023
MonotonicityNot monotonic
2023-06-15T12:30:33.629608image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2434
 
8.2%
1.493731028 × 101215
 
0.1%
13569002 9
 
< 0.1%
1.493727074 × 10129
 
< 0.1%
393486 8
 
< 0.1%
269212 8
 
< 0.1%
7618218 8
 
< 0.1%
1.493731028 × 10127
 
< 0.1%
1.49373106 × 10127
 
< 0.1%
1.49373074 × 10127
 
< 0.1%
Other values (22252) 27122
91.5%
ValueCountFrequency (%)
0 2434
8.2%
14160 1
 
< 0.1%
15161 1
 
< 0.1%
56256 1
 
< 0.1%
56905 1
 
< 0.1%
ValueCountFrequency (%)
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732897 × 10121
< 0.1%
1.493732894 × 10121
< 0.1%

dst2src_duration_ms
Real number (ℝ)

Distinct9645
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14143.32608
Minimum0
Maximum1799261
Zeros4874
Zeros (%)16.4%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:34.156294image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1522
median5684
Q37077
95-th percentile13763
Maximum1799261
Range1799261
Interquartile range (IQR)6555

Descriptive statistics

Standard deviation106706.5923
Coefficient of variation (CV)7.54466041
Kurtosis227.7392036
Mean14143.32608
Median Absolute Deviation (MAD)3356.5
Skewness14.76684684
Sum419123325
Variance1.138629685 × 1010
MonotonicityNot monotonic
2023-06-15T12:30:34.942669image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4874
 
16.4%
5245 19
 
0.1%
6217 18
 
0.1%
5783 15
 
0.1%
6333 15
 
0.1%
5756 14
 
< 0.1%
5977 14
 
< 0.1%
5946 14
 
< 0.1%
5809 14
 
< 0.1%
6129 14
 
< 0.1%
Other values (9635) 24623
83.1%
ValueCountFrequency (%)
0 4874
16.4%
1 1
 
< 0.1%
2 1
 
< 0.1%
3 3
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
1799261 1
< 0.1%
1798352 1
< 0.1%
1798350 1
< 0.1%
1798310 1
< 0.1%
1798125 1
< 0.1%

dst2src_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct193
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.43085645
Minimum0
Maximum120378
Zeros2434
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:35.396136image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile8
Maximum120378
Range120378
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1224.182227
Coefficient of variation (CV)54.57581302
Kurtosis6320.074383
Mean22.43085645
Median Absolute Deviation (MAD)1
Skewness77.4217371
Sum664716
Variance1498622.126
MonotonicityNot monotonic
2023-06-15T12:30:35.844054image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 14396
48.6%
2 7279
24.6%
0 2434
 
8.2%
1 2427
 
8.2%
4 762
 
2.6%
5 316
 
1.1%
6 287
 
1.0%
7 218
 
0.7%
8 188
 
0.6%
9 135
 
0.5%
Other values (183) 1192
 
4.0%
ValueCountFrequency (%)
0 2434
 
8.2%
1 2427
 
8.2%
2 7279
24.6%
3 14396
48.6%
4 762
 
2.6%
ValueCountFrequency (%)
120378 1
< 0.1%
92794 2
< 0.1%
74533 2
< 0.1%
27275 2
< 0.1%
6534 2
< 0.1%

dst2src_bytes
Real number (ℝ)

SKEWED  ZEROS 

Distinct1666
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11412.16937
Minimum0
Maximum108240611
Zeros2434
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:36.255227image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1136
median166
Q3166
95-th percentile1244
Maximum108240611
Range108240611
Interquartile range (IQR)30

Descriptive statistics

Standard deviation930820.0258
Coefficient of variation (CV)81.56381105
Kurtosis12467.48445
Mean11412.16937
Median Absolute Deviation (MAD)30
Skewness109.3421637
Sum338188227
Variance8.664259205 × 1011
MonotonicityNot monotonic
2023-06-15T12:30:36.720227image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
166 12680
42.8%
136 6920
23.4%
0 2434
 
8.2%
202 790
 
2.7%
58 760
 
2.6%
206 514
 
1.7%
317 513
 
1.7%
256 422
 
1.4%
54 367
 
1.2%
198 359
 
1.2%
Other values (1656) 3875
 
13.1%
ValueCountFrequency (%)
0 2434
8.2%
54 367
 
1.2%
58 760
 
2.6%
62 1
 
< 0.1%
66 131
 
0.4%
ValueCountFrequency (%)
108240611 2
< 0.1%
40859368 1
< 0.1%
16685359 2
< 0.1%
1951075 2
< 0.1%
1277352 1
< 0.1%

bidirectional_min_ps
Real number (ℝ)

Distinct84
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.07417156
Minimum54
Maximum590
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:37.162806image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile54
Q154
median54
Q366
95-th percentile143
Maximum590
Range536
Interquartile range (IQR)12

Descriptive statistics

Standard deviation28.2250544
Coefficient of variation (CV)0.420803623
Kurtosis59.92838221
Mean67.07417156
Median Absolute Deviation (MAD)0
Skewness5.28945288
Sum1987676
Variance796.6536959
MonotonicityNot monotonic
2023-06-15T12:30:37.627586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54 15441
52.1%
66 10700
36.1%
143 1948
 
6.6%
62 397
 
1.3%
74 299
 
1.0%
148 288
 
1.0%
171 103
 
0.3%
70 83
 
0.3%
90 62
 
0.2%
146 55
 
0.2%
Other values (74) 258
 
0.9%
ValueCountFrequency (%)
54 15441
52.1%
56 1
 
< 0.1%
58 2
 
< 0.1%
62 397
 
1.3%
64 10
 
< 0.1%
ValueCountFrequency (%)
590 12
< 0.1%
512 1
 
< 0.1%
467 1
 
< 0.1%
424 1
 
< 0.1%
423 1
 
< 0.1%

bidirectional_mean_ps
Real number (ℝ)

Distinct2230
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.15566162
Minimum54
Maximum1185.085932
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:38.132818image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile55.71428571
Q156.28571429
median66
Q368
95-th percentile230
Maximum1185.085932
Range1131.085932
Interquartile range (IQR)11.71428571

Descriptive statistics

Standard deviation94.15418044
Coefficient of variation (CV)1.044351278
Kurtosis33.9111131
Mean90.15566162
Median Absolute Deviation (MAD)9.714285714
Skewness5.21463995
Sum2671672.876
Variance8865.009695
MonotonicityNot monotonic
2023-06-15T12:30:38.601806image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56.28571429 6434
21.7%
68 6428
21.7%
55.71428571 5543
18.7%
143 978
 
3.3%
67.71428571 680
 
2.3%
66 620
 
2.1%
230 556
 
1.9%
58 552
 
1.9%
56.5 548
 
1.8%
68.4 531
 
1.8%
Other values (2220) 6764
22.8%
ValueCountFrequency (%)
54 27
 
0.1%
54.5 48
 
0.2%
55.33333333 1
 
< 0.1%
55.71428571 5543
18.7%
56.22222222 3
 
< 0.1%
ValueCountFrequency (%)
1185.085932 2
< 0.1%
1161.603687 1
< 0.1%
1131.268695 1
< 0.1%
1098.677815 1
< 0.1%
1082.750674 1
< 0.1%

bidirectional_stddev_ps
Real number (ℝ)

Distinct2332
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.88207268
Minimum0
Maximum728.1035406
Zeros2275
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:39.020487image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.14718317
median3.346640106
Q34.535573676
95-th percentile205.5646089
Maximum728.1035406
Range728.1035406
Interquartile range (IQR)1.388390506

Descriptive statistics

Standard deviation114.0204798
Coefficient of variation (CV)3.268741534
Kurtosis18.61061298
Mean34.88207268
Median Absolute Deviation (MAD)0.6533598939
Skewness4.309423539
Sum1033695.342
Variance13000.6698
MonotonicityNot monotonic
2023-06-15T12:30:39.460611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.535573676 6434
21.7%
3.346640106 6184
20.9%
3.14718317 5543
18.7%
0 2275
 
7.7%
3.14718317 676
 
2.3%
4 581
 
2.0%
3.577708764 548
 
1.8%
3.664501525 548
 
1.8%
123.0365799 498
 
1.7%
14.14213562 343
 
1.2%
Other values (2322) 6004
20.3%
ValueCountFrequency (%)
0 2275
7.7%
0.5006958946 40
 
0.1%
0.5007199428 2
 
< 0.1%
0.5007283325 2
 
< 0.1%
0.5007326011 1
 
< 0.1%
ValueCountFrequency (%)
728.1035406 1
< 0.1%
723.849159 1
< 0.1%
723.6323307 1
< 0.1%
722.2813896 1
< 0.1%
721.0381235 1
< 0.1%

bidirectional_max_ps
Real number (ℝ)

Distinct553
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157.223932
Minimum54
Maximum1514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:39.973682image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile62
Q166
median74
Q374
95-th percentile710
Maximum1514
Range1460
Interquartile range (IQR)8

Descriptive statistics

Standard deviation299.9882761
Coefficient of variation (CV)1.90803189
Kurtosis14.21083278
Mean157.223932
Median Absolute Deviation (MAD)8
Skewness3.897837534
Sum4659174
Variance89992.96581
MonotonicityNot monotonic
2023-06-15T12:30:40.465039image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74 9950
33.6%
62 7126
24.0%
66 6698
22.6%
1514 1058
 
3.6%
143 978
 
3.3%
70 696
 
2.3%
317 596
 
2.0%
148 287
 
1.0%
327 232
 
0.8%
308 114
 
0.4%
Other values (543) 1899
 
6.4%
ValueCountFrequency (%)
54 27
 
0.1%
55 48
 
0.2%
62 7126
24.0%
64 10
 
< 0.1%
66 6698
22.6%
ValueCountFrequency (%)
1514 1058
3.6%
1506 9
 
< 0.1%
1498 2
 
< 0.1%
1495 1
 
< 0.1%
1494 5
 
< 0.1%

src2dst_min_ps
Real number (ℝ)

Distinct83
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.65893906
Minimum54
Maximum590
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:41.048425image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile54
Q154
median66
Q366
95-th percentile143
Maximum590
Range536
Interquartile range (IQR)12

Descriptive statistics

Standard deviation28.15735723
Coefficient of variation (CV)0.4161661064
Kurtosis60.12077185
Mean67.65893906
Median Absolute Deviation (MAD)12
Skewness5.278915737
Sum2005005
Variance792.8367663
MonotonicityNot monotonic
2023-06-15T12:30:41.619437image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54 14267
48.1%
66 11433
38.6%
143 1948
 
6.6%
74 682
 
2.3%
62 400
 
1.3%
148 288
 
1.0%
171 103
 
0.3%
70 88
 
0.3%
146 69
 
0.2%
90 62
 
0.2%
Other values (73) 294
 
1.0%
ValueCountFrequency (%)
54 14267
48.1%
55 48
 
0.2%
58 2
 
< 0.1%
62 400
 
1.3%
64 10
 
< 0.1%
ValueCountFrequency (%)
590 12
< 0.1%
512 1
 
< 0.1%
467 1
 
< 0.1%
424 1
 
< 0.1%
423 1
 
< 0.1%

src2dst_mean_ps
Real number (ℝ)

Distinct1554
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.05077582
Minimum54
Maximum1496.22811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:42.172968image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile56
Q157
median67.6
Q368
95-th percentile145.0617647
Maximum1496.22811
Range1442.22811
Interquartile range (IQR)11

Descriptive statistics

Standard deviation81.84578683
Coefficient of variation (CV)1.009808802
Kurtosis112.7155659
Mean81.05077582
Median Absolute Deviation (MAD)10.6
Skewness9.275206174
Sum2401858.691
Variance6698.732822
MonotonicityNot monotonic
2023-06-15T12:30:42.656690image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68 7713
26.0%
57 6434
21.7%
56 5543
18.7%
143 1944
 
6.6%
68.66666667 1009
 
3.4%
74 679
 
2.3%
58 659
 
2.2%
67.6 621
 
2.1%
57.2 551
 
1.9%
70 322
 
1.1%
Other values (1544) 4159
14.0%
ValueCountFrequency (%)
54 27
 
0.1%
55 48
 
0.2%
55.6 1
 
< 0.1%
56 5543
18.7%
56.85714286 1
 
< 0.1%
ValueCountFrequency (%)
1496.22811 2
< 0.1%
1456.585366 1
< 0.1%
1433.402062 1
< 0.1%
1432.439153 1
< 0.1%
1411.920915 1
< 0.1%

src2dst_stddev_ps
Real number (ℝ)

Distinct1580
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.71138727
Minimum0
Maximum1018.233765
Zeros3734
Zeros (%)12.6%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:43.127582image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median4
Q36
95-th percentile34.64823228
Maximum1018.233765
Range1018.233765
Interquartile range (IQR)2

Descriptive statistics

Standard deviation83.02576143
Coefficient of variation (CV)4.212070936
Kurtosis39.10422589
Mean19.71138727
Median Absolute Deviation (MAD)0.6188021535
Skewness6.145474837
Sum584127.2503
Variance6893.277061
MonotonicityNot monotonic
2023-06-15T12:30:43.555158image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 7310
24.7%
6 6434
21.7%
4 5543
18.7%
0 3734
12.6%
4.618802154 989
 
3.3%
5.656854249 727
 
2.5%
3.577708764 620
 
2.1%
4.38178046 551
 
1.9%
2.828427125 391
 
1.3%
2.309401077 236
 
0.8%
Other values (1570) 3099
10.5%
ValueCountFrequency (%)
0 3734
12.6%
0.5913770168 1
 
< 0.1%
0.6859943406 1
 
< 0.1%
0.7302967433 1
 
< 0.1%
0.755928946 1
 
< 0.1%
ValueCountFrequency (%)
1018.233765 1
< 0.1%
747.5126755 1
< 0.1%
734.7095987 1
< 0.1%
730.2897446 1
< 0.1%
729.1732598 1
< 0.1%

src2dst_max_ps
Real number (ℝ)

Distinct574
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.7111089
Minimum54
Maximum1514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:44.055712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile62
Q166
median74
Q374
95-th percentile192
Maximum1514
Range1460
Interquartile range (IQR)8

Descriptive statistics

Standard deviation219.5813333
Coefficient of variation (CV)1.849711753
Kurtosis30.40809887
Mean118.7111089
Median Absolute Deviation (MAD)8
Skewness5.503229254
Sum3517885
Variance48215.96193
MonotonicityNot monotonic
2023-06-15T12:30:44.442642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74 10588
35.7%
62 7135
24.1%
66 6699
22.6%
143 1962
 
6.6%
70 698
 
2.4%
1514 502
 
1.7%
148 289
 
1.0%
171 104
 
0.4%
134 91
 
0.3%
146 52
 
0.2%
Other values (564) 1514
 
5.1%
ValueCountFrequency (%)
54 27
 
0.1%
55 48
 
0.2%
62 7135
24.1%
64 10
 
< 0.1%
66 6699
22.6%
ValueCountFrequency (%)
1514 502
1.7%
1506 5
 
< 0.1%
1498 1
 
< 0.1%
1495 1
 
< 0.1%
1494 2
 
< 0.1%

dst2src_min_ps
Real number (ℝ)

Distinct38
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.35040831
Minimum0
Maximum452
Zeros2434
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:44.895127image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q154
median54
Q366
95-th percentile66
Maximum452
Range452
Interquartile range (IQR)12

Descriptive statistics

Standard deviation51.22941657
Coefficient of variation (CV)0.808667504
Kurtosis18.98471596
Mean63.35040831
Median Absolute Deviation (MAD)4
Skewness4.154140045
Sum1877326
Variance2624.453122
MonotonicityNot monotonic
2023-06-15T12:30:45.405407image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
54 14232
48.0%
66 10871
36.7%
0 2434
 
8.2%
58 762
 
2.6%
317 590
 
2.0%
327 232
 
0.8%
70 216
 
0.7%
308 112
 
0.4%
74 49
 
0.2%
339 28
 
0.1%
Other values (28) 108
 
0.4%
ValueCountFrequency (%)
0 2434
 
8.2%
54 14232
48.0%
56 1
 
< 0.1%
58 762
 
2.6%
62 9
 
< 0.1%
ValueCountFrequency (%)
452 2
< 0.1%
396 2
< 0.1%
381 2
< 0.1%
375 2
< 0.1%
373 4
< 0.1%

dst2src_mean_ps
Real number (ℝ)

Distinct1720
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.6956822
Minimum0
Maximum1482.047328
Zeros2434
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:45.954645image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q155.33333333
median55.33333333
Q368
95-th percentile317
Maximum1482.047328
Range1482.047328
Interquartile range (IQR)12.66666667

Descriptive statistics

Standard deviation129.2607739
Coefficient of variation (CV)1.50836974
Kurtosis45.38430472
Mean85.6956822
Median Absolute Deviation (MAD)10.66666667
Skewness6.062376459
Sum2539505.846
Variance16708.34766
MonotonicityNot monotonic
2023-06-15T12:30:46.442915image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55.33333333 12680
42.8%
68 6987
23.6%
0 2434
 
8.2%
66 879
 
3.0%
67.33333333 790
 
2.7%
58 765
 
2.6%
317 590
 
2.0%
68.66666667 514
 
1.7%
64 423
 
1.4%
54 423
 
1.4%
Other values (1710) 3149
 
10.6%
ValueCountFrequency (%)
0 2434
8.2%
54 423
 
1.4%
54.72727273 1
 
< 0.1%
54.8 4
 
< 0.1%
54.85714286 1
 
< 0.1%
ValueCountFrequency (%)
1482.047328 1
< 0.1%
1479.712963 1
< 0.1%
1472.297143 1
< 0.1%
1469.846154 1
< 0.1%
1464.574627 1
< 0.1%

dst2src_stddev_ps
Real number (ℝ)

Distinct1757
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.21764493
Minimum0
Maximum745.4010106
Zeros5799
Zeros (%)19.6%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:46.942551image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.309401077
median2.309401077
Q32.828427125
95-th percentile155.6440482
Maximum745.4010106
Range745.4010106
Interquartile range (IQR)0.519026048

Descriptive statistics

Standard deviation103.7416672
Coefficient of variation (CV)4.113852324
Kurtosis24.76125004
Mean25.21764493
Median Absolute Deviation (MAD)0.519026048
Skewness4.981708303
Sum747299.6897
Variance10762.33351
MonotonicityNot monotonic
2023-06-15T12:30:47.693592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.309401077 12680
42.8%
2.828427125 6923
23.4%
0 5799
19.6%
2.309401077 790
 
2.7%
2.309401077 486
 
1.6%
6.92820323 421
 
1.4%
4.618802154 85
 
0.3%
6.889605697 67
 
0.2%
2 62
 
0.2%
6.066300355 60
 
0.2%
Other values (1747) 2261
 
7.6%
ValueCountFrequency (%)
0 5799
19.6%
0.7612788284 1
 
< 0.1%
0.8866830869 1
 
< 0.1%
0.8866830869 1
 
< 0.1%
0.9428090416 1
 
< 0.1%
ValueCountFrequency (%)
745.4010106 1
< 0.1%
741.9907585 1
< 0.1%
733.5978917 1
< 0.1%
730.9474445 1
< 0.1%
728.6032702 1
< 0.1%

dst2src_max_ps
Real number (ℝ)

Distinct520
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.0142404
Minimum0
Maximum1514
Zeros2434
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:48.201123image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q158
median58
Q370
95-th percentile472
Maximum1514
Range1514
Interquartile range (IQR)12

Descriptive statistics

Standard deviation263.0617025
Coefficient of variation (CV)2.087555356
Kurtosis19.36766258
Mean126.0142404
Median Absolute Deviation (MAD)8
Skewness4.422645023
Sum3734306
Variance69201.45932
MonotonicityNot monotonic
2023-06-15T12:30:48.825884image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58 13480
45.5%
70 9097
30.7%
0 2434
 
8.2%
66 891
 
3.0%
1514 686
 
2.3%
317 596
 
2.0%
54 423
 
1.4%
327 232
 
0.8%
74 201
 
0.7%
308 114
 
0.4%
Other values (510) 1480
 
5.0%
ValueCountFrequency (%)
0 2434
 
8.2%
54 423
 
1.4%
58 13480
45.5%
60 3
 
< 0.1%
61 27
 
0.1%
ValueCountFrequency (%)
1514 686
2.3%
1506 4
 
< 0.1%
1500 1
 
< 0.1%
1498 1
 
< 0.1%
1494 5
 
< 0.1%

bidirectional_min_piat_ms
Real number (ℝ)

SKEWED  ZEROS 

Distinct866
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158.2613552
Minimum0
Maximum116629
Zeros14222
Zeros (%)48.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:49.383019image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile290
Maximum116629
Range116629
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2358.625712
Coefficient of variation (CV)14.90335849
Kurtosis1305.863603
Mean158.2613552
Median Absolute Deviation (MAD)1
Skewness34.06813685
Sum4689917
Variance5563115.247
MonotonicityNot monotonic
2023-06-15T12:30:49.923317image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14222
48.0%
1 8736
29.5%
2 2556
 
8.6%
3 393
 
1.3%
4 92
 
0.3%
997 58
 
0.2%
998 49
 
0.2%
5 37
 
0.1%
999 35
 
0.1%
6 35
 
0.1%
Other values (856) 3421
 
11.5%
ValueCountFrequency (%)
0 14222
48.0%
1 8736
29.5%
2 2556
 
8.6%
3 393
 
1.3%
4 92
 
0.3%
ValueCountFrequency (%)
116629 1
< 0.1%
116487 1
< 0.1%
96031 2
< 0.1%
95956 2
< 0.1%
95263 2
< 0.1%
Distinct16594
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1372.810094
Minimum0
Maximum116629
Zeros1339
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:50.450451image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.94166667
Q1277.8421053
median1048
Q31351.660714
95-th percentile3402.161429
Maximum116629
Range116629
Interquartile range (IQR)1073.818609

Descriptive statistics

Standard deviation3327.560762
Coefficient of variation (CV)2.423904644
Kurtosis366.403334
Mean1372.810094
Median Absolute Deviation (MAD)524.7083333
Skewness15.82257125
Sum40681854.33
Variance11072660.63
MonotonicityNot monotonic
2023-06-15T12:30:51.130291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1339
 
4.5%
41 21
 
0.1%
46 20
 
0.1%
3002 19
 
0.1%
42 19
 
0.1%
106 18
 
0.1%
45 18
 
0.1%
43 18
 
0.1%
1501 17
 
0.1%
118 17
 
0.1%
Other values (16584) 28128
94.9%
ValueCountFrequency (%)
0 1339
4.5%
1 4
 
< 0.1%
1.943708609 1
 
< 0.1%
2.5 2
 
< 0.1%
3 3
 
< 0.1%
ValueCountFrequency (%)
116629 1
< 0.1%
116487 1
< 0.1%
96031 2
< 0.1%
95956 2
< 0.1%
95263 2
< 0.1%
Distinct26034
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2319.755897
Minimum0
Maximum67938.81954
Zeros2808
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:51.635981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1308.1649688
median2343.003176
Q32820.196512
95-th percentile5178.442387
Maximum67938.81954
Range67938.81954
Interquartile range (IQR)2512.031543

Descriptive statistics

Standard deviation3245.284158
Coefficient of variation (CV)1.398976574
Kurtosis112.6909131
Mean2319.755897
Median Absolute Deviation (MAD)1107.69058
Skewness8.251151974
Sum68743646.24
Variance10531869.26
MonotonicityNot monotonic
2023-06-15T12:30:52.165584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2808
 
9.5%
2122.02745 13
 
< 0.1%
712.0565287 9
 
< 0.1%
2112.127955 8
 
< 0.1%
711.3494219 8
 
< 0.1%
2126.270091 8
 
< 0.1%
2112.835062 8
 
< 0.1%
2114.249276 7
 
< 0.1%
2114.956383 7
 
< 0.1%
2122.734557 7
 
< 0.1%
Other values (26024) 26751
90.3%
ValueCountFrequency (%)
0 2808
9.5%
0.7071067812 4
 
< 0.1%
2.828427125 1
 
< 0.1%
2.880972058 1
 
< 0.1%
3.386246693 1
 
< 0.1%
ValueCountFrequency (%)
67938.81954 2
< 0.1%
65676.78494 1
< 0.1%
61731.83621 2
< 0.1%
61562.13058 2
< 0.1%
60271.66071 2
< 0.1%

bidirectional_max_piat_ms
Real number (ℝ)

Distinct9308
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5895.338058
Minimum0
Maximum119378
Zeros1339
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:52.707049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30
Q1859
median5668.5
Q36910
95-th percentile12878.35
Maximum119378
Range119378
Interquartile range (IQR)6051

Descriptive statistics

Standard deviation8274.361466
Coefficient of variation (CV)1.40354317
Kurtosis50.20667083
Mean5895.338058
Median Absolute Deviation (MAD)2768.5
Skewness5.897940806
Sum174702448
Variance68465057.66
MonotonicityNot monotonic
2023-06-15T12:30:53.241323image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1339
 
4.5%
32064 65
 
0.2%
2004 37
 
0.1%
3002 31
 
0.1%
32032 28
 
0.1%
999 26
 
0.1%
179 26
 
0.1%
6001 25
 
0.1%
6004 25
 
0.1%
85 24
 
0.1%
Other values (9298) 28008
94.5%
ValueCountFrequency (%)
0 1339
4.5%
1 4
 
< 0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
6 3
 
< 0.1%
ValueCountFrequency (%)
119378 1
< 0.1%
118059 1
< 0.1%
116998 1
< 0.1%
116629 1
< 0.1%
116487 1
< 0.1%

src2dst_min_piat_ms
Real number (ℝ)

SKEWED  ZEROS 

Distinct2335
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean493.2481946
Minimum0
Maximum116629
Zeros4337
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:53.675909image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median14
Q385
95-th percentile2319.5
Maximum116629
Range116629
Interquartile range (IQR)78

Descriptive statistics

Standard deviation3436.121656
Coefficient of variation (CV)6.966313701
Kurtosis558.5160993
Mean493.2481946
Median Absolute Deviation (MAD)12
Skewness21.58656427
Sum14616917
Variance11806932.04
MonotonicityNot monotonic
2023-06-15T12:30:54.119796image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4337
 
14.6%
10 1238
 
4.2%
9 1186
 
4.0%
11 1151
 
3.9%
12 1071
 
3.6%
8 989
 
3.3%
13 982
 
3.3%
7 802
 
2.7%
14 796
 
2.7%
15 744
 
2.5%
Other values (2325) 16338
55.1%
ValueCountFrequency (%)
0 4337
14.6%
1 124
 
0.4%
2 208
 
0.7%
3 564
 
1.9%
4 573
 
1.9%
ValueCountFrequency (%)
116629 1
< 0.1%
116487 1
< 0.1%
100607 2
< 0.1%
100558 2
< 0.1%
96213 2
< 0.1%

src2dst_mean_piat_ms
Real number (ℝ)

Distinct13626
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2353.710984
Minimum0
Maximum116629
Zeros2645
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:54.554052image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1465.8125
median1991.166667
Q32644.666667
95-th percentile5833.3
Maximum116629
Range116629
Interquartile range (IQR)2178.854167

Descriptive statistics

Standard deviation4465.640609
Coefficient of variation (CV)1.89727653
Kurtosis213.8059259
Mean2353.710984
Median Absolute Deviation (MAD)1065.166667
Skewness12.42170259
Sum69749871.3
Variance19941946.05
MonotonicityNot monotonic
2023-06-15T12:30:54.927348image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2645
 
8.9%
85 29
 
0.1%
3002 22
 
0.1%
1996.333333 18
 
0.1%
2009.333333 16
 
0.1%
1501 16
 
0.1%
2012.333333 15
 
0.1%
2028.333333 15
 
0.1%
2019 14
 
< 0.1%
1996 14
 
< 0.1%
Other values (13616) 26830
90.5%
ValueCountFrequency (%)
0 2645
8.9%
1 4
 
< 0.1%
2.5 1
 
< 0.1%
4.284671533 1
 
< 0.1%
4.4 1
 
< 0.1%
ValueCountFrequency (%)
116629 1
< 0.1%
116487 1
< 0.1%
100607 2
< 0.1%
100558 2
< 0.1%
96213 2
< 0.1%

src2dst_stddev_piat_ms
Real number (ℝ)

Distinct23662
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2842.017462
Minimum0
Maximum65676.78494
Zeros4274
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:55.504182image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1239.7166278
median3039.531268
Q33845.154483
95-th percentile6859.229139
Maximum65676.78494
Range65676.78494
Interquartile range (IQR)3605.437855

Descriptive statistics

Standard deviation3543.56455
Coefficient of variation (CV)1.246848268
Kurtosis97.79081624
Mean2842.017462
Median Absolute Deviation (MAD)1706.832605
Skewness7.101269261
Sum84220345.47
Variance12556849.72
MonotonicityNot monotonic
2023-06-15T12:30:56.007091image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4274
 
14.4%
2122.02745 13
 
< 0.1%
2122.734557 9
 
< 0.1%
2112.835062 8
 
< 0.1%
2126.270091 8
 
< 0.1%
0.7071067812 8
 
< 0.1%
2114.249276 8
 
< 0.1%
712.0565287 8
 
< 0.1%
711.3494219 8
 
< 0.1%
2112.127955 8
 
< 0.1%
Other values (23652) 25282
85.3%
ValueCountFrequency (%)
0 4274
14.4%
0.5773502692 2
 
< 0.1%
0.7071067812 8
 
< 0.1%
1 1
 
< 0.1%
1.154700538 3
 
< 0.1%
ValueCountFrequency (%)
65676.78494 1
< 0.1%
65379.8001 2
< 0.1%
65376.26456 2
< 0.1%
63504.55291 2
< 0.1%
63445.15594 2
< 0.1%

src2dst_max_piat_ms
Real number (ℝ)

Distinct9501
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5953.493386
Minimum0
Maximum119378
Zeros2645
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:56.492982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1974.25
median5694
Q36939
95-th percentile13104.1
Maximum119378
Range119378
Interquartile range (IQR)5964.75

Descriptive statistics

Standard deviation8281.498531
Coefficient of variation (CV)1.391031785
Kurtosis49.55351215
Mean5953.493386
Median Absolute Deviation (MAD)2706
Skewness5.84875711
Sum176425823
Variance68583217.91
MonotonicityNot monotonic
2023-06-15T12:30:57.014963image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2645
 
8.9%
32064 65
 
0.2%
2004 36
 
0.1%
3002 33
 
0.1%
32032 28
 
0.1%
6002 26
 
0.1%
6001 25
 
0.1%
6004 25
 
0.1%
5997 23
 
0.1%
5996 23
 
0.1%
Other values (9491) 26705
90.1%
ValueCountFrequency (%)
0 2645
8.9%
1 4
 
< 0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
6 3
 
< 0.1%
ValueCountFrequency (%)
119378 1
< 0.1%
118059 1
< 0.1%
116998 1
< 0.1%
116629 1
< 0.1%
116487 1
< 0.1%

dst2src_min_piat_ms
Real number (ℝ)

Distinct4043
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1016.324425
Minimum0
Maximum100774
Zeros7207
Zeros (%)24.3%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:57.490578image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median13
Q3617.75
95-th percentile5874.35
Maximum100774
Range100774
Interquartile range (IQR)616.75

Descriptive statistics

Standard deviation2911.422368
Coefficient of variation (CV)2.864658467
Kurtosis443.4503987
Mean1016.324425
Median Absolute Deviation (MAD)13
Skewness15.34418767
Sum30117758
Variance8476380.205
MonotonicityNot monotonic
2023-06-15T12:30:57.982417image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7207
24.3%
7 929
 
3.1%
8 887
 
3.0%
6 874
 
2.9%
9 845
 
2.9%
10 796
 
2.7%
5 678
 
2.3%
11 616
 
2.1%
12 547
 
1.8%
13 476
 
1.6%
Other values (4033) 15779
53.2%
ValueCountFrequency (%)
0 7207
24.3%
1 271
 
0.9%
2 137
 
0.5%
3 199
 
0.7%
4 415
 
1.4%
ValueCountFrequency (%)
100774 2
< 0.1%
100651 2
< 0.1%
100630 2
< 0.1%
93138 2
< 0.1%
92913 2
< 0.1%

dst2src_mean_piat_ms
Real number (ℝ)

Distinct11426
Distinct (%)38.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2842.696158
Minimum0
Maximum100774
Zeros4874
Zeros (%)16.4%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:58.509558image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1321
median2918.5
Q34092.875
95-th percentile6449
Maximum100774
Range100774
Interquartile range (IQR)3771.875

Descriptive statistics

Standard deviation3714.793355
Coefficient of variation (CV)1.306785231
Kurtosis204.4296123
Mean2842.696158
Median Absolute Deviation (MAD)2199.5
Skewness10.47263837
Sum84240457.95
Variance13799689.67
MonotonicityNot monotonic
2023-06-15T12:30:58.938945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4874
 
16.4%
3166.5 14
 
< 0.1%
197 13
 
< 0.1%
2819 12
 
< 0.1%
3069.5 12
 
< 0.1%
3108.5 12
 
< 0.1%
5245 12
 
< 0.1%
3064.5 12
 
< 0.1%
3031 11
 
< 0.1%
79 11
 
< 0.1%
Other values (11416) 24651
83.2%
ValueCountFrequency (%)
0 4874
16.4%
1 1
 
< 0.1%
2 1
 
< 0.1%
3 3
 
< 0.1%
3.243902439 1
 
< 0.1%
ValueCountFrequency (%)
100774 2
< 0.1%
100651 2
< 0.1%
100630 2
< 0.1%
93138 2
< 0.1%
92913 2
< 0.1%

dst2src_stddev_piat_ms
Real number (ℝ)

Distinct9879
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2554.297605
Minimum0
Maximum65256.76352
Zeros12142
Zeros (%)41.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:30:59.359406image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median733.6232855
Q34510.634157
95-th percentile7433.848946
Maximum65256.76352
Range65256.76352
Interquartile range (IQR)4510.634157

Descriptive statistics

Standard deviation3493.909073
Coefficient of variation (CV)1.367855126
Kurtosis64.86981212
Mean2554.297605
Median Absolute Deviation (MAD)733.6232855
Skewness4.93946741
Sum75694055.23
Variance12207400.61
MonotonicityNot monotonic
2023-06-15T12:30:59.817489image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12142
41.0%
4468.20775 15
 
0.1%
4089.198516 13
 
< 0.1%
4273.753385 12
 
< 0.1%
4183.950824 12
 
< 0.1%
4568.616913 11
 
< 0.1%
4277.996026 11
 
< 0.1%
4202.335601 11
 
< 0.1%
4332.443248 11
 
< 0.1%
4205.164028 11
 
< 0.1%
Other values (9869) 17385
58.7%
ValueCountFrequency (%)
0 12142
41.0%
0.7071067812 7
 
< 0.1%
1.414213562 1
 
< 0.1%
2.121320344 4
 
< 0.1%
2.828427125 9
 
< 0.1%
ValueCountFrequency (%)
65256.76352 2
< 0.1%
65235.55031 2
< 0.1%
63432.42802 2
< 0.1%
62714.00753 2
< 0.1%
61993.46572 2
< 0.1%

dst2src_max_piat_ms
Real number (ℝ)

Distinct8747
Distinct (%)29.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5011.329621
Minimum0
Maximum116992
Zeros4874
Zeros (%)16.4%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:00.270034image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1474.25
median5549
Q36740
95-th percentile11152.05
Maximum116992
Range116992
Interquartile range (IQR)6265.75

Descriptive statistics

Standard deviation6597.276909
Coefficient of variation (CV)1.316472355
Kurtosis72.26707772
Mean5011.329621
Median Absolute Deviation (MAD)3324
Skewness6.73721607
Sum148505742
Variance43524062.62
MonotonicityNot monotonic
2023-06-15T12:31:01.009975image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4874
 
16.4%
999 26
 
0.1%
1000 21
 
0.1%
5812 19
 
0.1%
184 18
 
0.1%
5792 18
 
0.1%
6019 17
 
0.1%
5856 17
 
0.1%
5783 16
 
0.1%
5999 16
 
0.1%
Other values (8737) 24592
83.0%
ValueCountFrequency (%)
0 4874
16.4%
1 1
 
< 0.1%
2 1
 
< 0.1%
3 3
 
< 0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
116992 1
< 0.1%
100774 2
< 0.1%
100651 2
< 0.1%
100630 2
< 0.1%
96583 2
< 0.1%

bidirectional_syn_packets
Real number (ℝ)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.87247756
Minimum0
Maximum9
Zeros3026
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:01.507704image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8427684063
Coefficient of variation (CV)0.4500819793
Kurtosis9.148897855
Mean1.87247756
Median Absolute Deviation (MAD)0
Skewness0.6225751644
Sum55489
Variance0.7102585866
MonotonicityNot monotonic
2023-06-15T12:31:01.922154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 22804
77.0%
0 3026
 
10.2%
3 1932
 
6.5%
1 1328
 
4.5%
4 308
 
1.0%
7 101
 
0.3%
5 55
 
0.2%
6 49
 
0.2%
8 30
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
0 3026
 
10.2%
1 1328
 
4.5%
2 22804
77.0%
3 1932
 
6.5%
4 308
 
1.0%
ValueCountFrequency (%)
9 1
 
< 0.1%
8 30
 
0.1%
7 101
0.3%
6 49
0.2%
5 55
0.2%

bidirectional_cwr_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros29634
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:02.359375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-15T12:31:02.737555image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%

bidirectional_ece_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros29634
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:03.142463image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-15T12:31:03.547317image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%

bidirectional_urg_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros29634
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:03.955660image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-15T12:31:04.442611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%

bidirectional_ack_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct252
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.48640076
Minimum0
Maximum392213
Zeros3488
Zeros (%)11.8%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:04.866770image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median6
Q36
95-th percentile14
Maximum392213
Range392213
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2662.763485
Coefficient of variation (CV)67.43495063
Kurtosis16405.70462
Mean39.48640076
Median Absolute Deviation (MAD)1
Skewness119.6243878
Sum1170140
Variance7090309.38
MonotonicityNot monotonic
2023-06-15T12:31:05.360902image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 13900
46.9%
5 6825
23.0%
0 3488
 
11.8%
1 1299
 
4.4%
4 737
 
2.5%
7 636
 
2.1%
3 266
 
0.9%
8 258
 
0.9%
9 198
 
0.7%
13 137
 
0.5%
Other values (242) 1890
 
6.4%
ValueCountFrequency (%)
0 3488
11.8%
1 1299
 
4.4%
2 67
 
0.2%
3 266
 
0.9%
4 737
 
2.5%
ValueCountFrequency (%)
392213 1
< 0.1%
124890 2
< 0.1%
110611 2
< 0.1%
16236 2
< 0.1%
6336 1
< 0.1%

bidirectional_psh_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct125
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.995275697
Minimum0
Maximum31175
Zeros27339
Zeros (%)92.3%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:05.874524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum31175
Range31175
Interquartile range (IQR)0

Descriptive statistics

Standard deviation189.7388203
Coefficient of variation (CV)63.34602873
Kurtosis24624.11003
Mean2.995275697
Median Absolute Deviation (MAD)0
Skewness151.3711071
Sum88762
Variance36000.81994
MonotonicityNot monotonic
2023-06-15T12:31:06.302220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27339
92.3%
2 460
 
1.6%
1 295
 
1.0%
4 240
 
0.8%
3 237
 
0.8%
5 167
 
0.6%
6 131
 
0.4%
7 95
 
0.3%
8 77
 
0.3%
11 72
 
0.2%
Other values (115) 521
 
1.8%
ValueCountFrequency (%)
0 27339
92.3%
1 295
 
1.0%
2 460
 
1.6%
3 237
 
0.8%
4 240
 
0.8%
ValueCountFrequency (%)
31175 1
< 0.1%
4857 2
< 0.1%
3284 2
< 0.1%
2810 1
< 0.1%
2142 1
< 0.1%

bidirectional_rst_packets
Real number (ℝ)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1053519606
Minimum0
Maximum10
Zeros27268
Zeros (%)92.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:06.614083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4287405019
Coefficient of variation (CV)4.069601548
Kurtosis73.40625872
Mean0.1053519606
Median Absolute Deviation (MAD)0
Skewness6.7281411
Sum3122
Variance0.1838184179
MonotonicityNot monotonic
2023-06-15T12:31:06.874382image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 27268
92.0%
1 1948
 
6.6%
3 185
 
0.6%
2 185
 
0.6%
4 25
 
0.1%
5 9
 
< 0.1%
6 5
 
< 0.1%
9 3
 
< 0.1%
7 3
 
< 0.1%
8 2
 
< 0.1%
ValueCountFrequency (%)
0 27268
92.0%
1 1948
 
6.6%
2 185
 
0.6%
3 185
 
0.6%
4 25
 
0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
9 3
< 0.1%
8 2
 
< 0.1%
7 3
< 0.1%
6 5
< 0.1%

bidirectional_fin_packets
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.67864615
Minimum0
Maximum8
Zeros4966
Zeros (%)16.8%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:07.134240image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q32
95-th percentile2
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8094693862
Coefficient of variation (CV)0.4822156155
Kurtosis1.946446728
Mean1.67864615
Median Absolute Deviation (MAD)0
Skewness-1.02026156
Sum49745
Variance0.6552406872
MonotonicityNot monotonic
2023-06-15T12:31:07.434467image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2 23108
78.0%
0 4966
 
16.8%
1 705
 
2.4%
3 686
 
2.3%
4 114
 
0.4%
5 32
 
0.1%
6 12
 
< 0.1%
7 10
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
0 4966
 
16.8%
1 705
 
2.4%
2 23108
78.0%
3 686
 
2.3%
4 114
 
0.4%
ValueCountFrequency (%)
8 1
 
< 0.1%
7 10
 
< 0.1%
6 12
 
< 0.1%
5 32
 
0.1%
4 114
0.4%

src2dst_syn_packets
Real number (ℝ)

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.009212391
Minimum0
Maximum7
Zeros3026
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:07.814645image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6385432555
Coefficient of variation (CV)0.6327144426
Kurtosis34.77890964
Mean1.009212391
Median Absolute Deviation (MAD)0
Skewness4.34043933
Sum29907
Variance0.4077374892
MonotonicityNot monotonic
2023-06-15T12:31:08.175987image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 24719
83.4%
0 3026
 
10.2%
2 1159
 
3.9%
3 492
 
1.7%
7 103
 
0.3%
5 55
 
0.2%
4 41
 
0.1%
6 39
 
0.1%
ValueCountFrequency (%)
0 3026
 
10.2%
1 24719
83.4%
2 1159
 
3.9%
3 492
 
1.7%
4 41
 
0.1%
ValueCountFrequency (%)
7 103
 
0.3%
6 39
 
0.1%
5 55
 
0.2%
4 41
 
0.1%
3 492
1.7%

src2dst_cwr_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros29634
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:08.524197image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-15T12:31:08.872653image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%

src2dst_ece_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros29634
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:09.143262image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-15T12:31:09.401225image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%

src2dst_urg_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros29634
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:09.667003image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-15T12:31:09.910339image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%

src2dst_ack_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct174
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.48960653
Minimum0
Maximum271835
Zeros4817
Zeros (%)16.3%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:10.247839image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median3
Q33
95-th percentile7
Maximum271835
Range271835
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1797.745964
Coefficient of variation (CV)76.53367722
Kurtosis18233.07662
Mean23.48960653
Median Absolute Deviation (MAD)0
Skewness128.000122
Sum696091
Variance3231890.552
MonotonicityNot monotonic
2023-06-15T12:31:10.725695image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 20463
69.1%
0 4817
 
16.3%
2 1341
 
4.5%
4 839
 
2.8%
5 252
 
0.9%
1 231
 
0.8%
7 219
 
0.7%
6 148
 
0.5%
8 140
 
0.5%
9 121
 
0.4%
Other values (164) 1063
 
3.6%
ValueCountFrequency (%)
0 4817
 
16.3%
1 231
 
0.8%
2 1341
 
4.5%
3 20463
69.1%
4 839
 
2.8%
ValueCountFrequency (%)
271835 1
< 0.1%
97615 2
< 0.1%
36078 2
< 0.1%
9702 2
< 0.1%
4351 1
< 0.1%

src2dst_psh_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct93
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.124654114
Minimum0
Maximum6653
Zeros27969
Zeros (%)94.4%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:11.171588image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6653
Range6653
Interquartile range (IQR)0

Descriptive statistics

Standard deviation49.02196539
Coefficient of variation (CV)43.58848183
Kurtosis12315.91781
Mean1.124654114
Median Absolute Deviation (MAD)0
Skewness101.3922025
Sum33328
Variance2403.15309
MonotonicityNot monotonic
2023-06-15T12:31:11.589030image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27969
94.4%
1 579
 
2.0%
2 336
 
1.1%
3 290
 
1.0%
4 121
 
0.4%
5 51
 
0.2%
6 34
 
0.1%
8 33
 
0.1%
7 26
 
0.1%
10 21
 
0.1%
Other values (83) 174
 
0.6%
ValueCountFrequency (%)
0 27969
94.4%
1 579
 
2.0%
2 336
 
1.1%
3 290
 
1.0%
4 121
 
0.4%
ValueCountFrequency (%)
6653 1
< 0.1%
2818 2
< 0.1%
1932 1
< 0.1%
1575 1
< 0.1%
1327 1
< 0.1%

src2dst_rst_packets
Real number (ℝ)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05527434703
Minimum0
Maximum10
Zeros28405
Zeros (%)95.9%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:11.884435image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.320160329
Coefficient of variation (CV)5.792204633
Kurtosis148.4569392
Mean0.05527434703
Median Absolute Deviation (MAD)0
Skewness9.663955053
Sum1638
Variance0.1025026362
MonotonicityNot monotonic
2023-06-15T12:31:12.141189image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 28405
95.9%
1 1019
 
3.4%
3 112
 
0.4%
2 71
 
0.2%
4 15
 
0.1%
6 4
 
< 0.1%
5 3
 
< 0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
0 28405
95.9%
1 1019
 
3.4%
2 71
 
0.2%
3 112
 
0.4%
4 15
 
0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
9 1
 
< 0.1%
8 2
< 0.1%
7 1
 
< 0.1%
6 4
< 0.1%

src2dst_fin_packets
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8201052845
Minimum0
Maximum7
Zeros5579
Zeros (%)18.8%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:12.394877image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4087087799
Coefficient of variation (CV)0.4983613539
Kurtosis3.324248259
Mean0.8201052845
Median Absolute Deviation (MAD)0
Skewness-1.030691058
Sum24303
Variance0.1670428668
MonotonicityNot monotonic
2023-06-15T12:31:12.642066image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 23833
80.4%
0 5579
 
18.8%
2 204
 
0.7%
3 14
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
0 5579
 
18.8%
1 23833
80.4%
2 204
 
0.7%
3 14
 
< 0.1%
4 2
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
5 1
 
< 0.1%
4 2
 
< 0.1%
3 14
 
< 0.1%
2 204
0.7%

dst2src_syn_packets
Real number (ℝ)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8632651684
Minimum0
Maximum6
Zeros5117
Zeros (%)17.3%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:12.923479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4442362885
Coefficient of variation (CV)0.514600038
Kurtosis3.124217429
Mean0.8632651684
Median Absolute Deviation (MAD)0
Skewness-0.3300564834
Sum25582
Variance0.19734588
MonotonicityNot monotonic
2023-06-15T12:31:13.157377image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
1 23556
79.5%
0 5117
 
17.3%
2 860
 
2.9%
3 100
 
0.3%
6 1
 
< 0.1%
ValueCountFrequency (%)
0 5117
 
17.3%
1 23556
79.5%
2 860
 
2.9%
3 100
 
0.3%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
3 100
 
0.3%
2 860
 
2.9%
1 23556
79.5%
0 5117
 
17.3%

dst2src_cwr_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros29634
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:13.424065image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-15T12:31:13.646993image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%

dst2src_ece_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros29634
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:13.882415image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-15T12:31:14.122828image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%

dst2src_urg_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros29634
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:14.490608image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-15T12:31:14.845500image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%

dst2src_ack_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct190
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.99679422
Minimum0
Maximum120378
Zeros3536
Zeros (%)11.9%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:15.248851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile7
Maximum120378
Range120378
Interquartile range (IQR)1

Descriptive statistics

Standard deviation957.9559812
Coefficient of variation (CV)59.8842473
Kurtosis10924.80098
Mean15.99679422
Median Absolute Deviation (MAD)1
Skewness100.2871145
Sum474049
Variance917679.6619
MonotonicityNot monotonic
2023-06-15T12:31:15.683297image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 14794
49.9%
2 7236
24.4%
0 3536
 
11.9%
1 1458
 
4.9%
4 482
 
1.6%
5 282
 
1.0%
6 221
 
0.7%
7 192
 
0.6%
8 155
 
0.5%
9 129
 
0.4%
Other values (180) 1149
 
3.9%
ValueCountFrequency (%)
0 3536
 
11.9%
1 1458
 
4.9%
2 7236
24.4%
3 14794
49.9%
4 482
 
1.6%
ValueCountFrequency (%)
120378 1
< 0.1%
74533 2
< 0.1%
27275 2
< 0.1%
6534 2
< 0.1%
1985 1
< 0.1%

dst2src_psh_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct98
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.870621583
Minimum0
Maximum24522
Zeros27650
Zeros (%)93.3%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:16.177262image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum24522
Range24522
Interquartile range (IQR)0

Descriptive statistics

Standard deviation145.8080563
Coefficient of variation (CV)77.94631343
Kurtosis27003.54309
Mean1.870621583
Median Absolute Deviation (MAD)0
Skewness161.1968137
Sum55434
Variance21259.98927
MonotonicityNot monotonic
2023-06-15T12:31:16.627319image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27650
93.3%
2 482
 
1.6%
1 422
 
1.4%
3 244
 
0.8%
4 183
 
0.6%
6 88
 
0.3%
5 76
 
0.3%
7 49
 
0.2%
8 48
 
0.2%
11 46
 
0.2%
Other values (88) 346
 
1.2%
ValueCountFrequency (%)
0 27650
93.3%
1 422
 
1.4%
2 482
 
1.6%
3 244
 
0.8%
4 183
 
0.6%
ValueCountFrequency (%)
24522 1
< 0.1%
2800 2
< 0.1%
2039 2
< 0.1%
908 2
< 0.1%
878 1
< 0.1%

dst2src_rst_packets
Real number (ℝ)

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05007761355
Minimum0
Maximum7
Zeros28474
Zeros (%)96.1%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:16.912109image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.283262662
Coefficient of variation (CV)5.656472861
Kurtosis89.07068841
Mean0.05007761355
Median Absolute Deviation (MAD)0
Skewness7.993111901
Sum1484
Variance0.08023773568
MonotonicityNot monotonic
2023-06-15T12:31:17.142457image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 28474
96.1%
1 952
 
3.2%
2 120
 
0.4%
3 71
 
0.2%
4 10
 
< 0.1%
5 4
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
0 28474
96.1%
1 952
 
3.2%
2 120
 
0.4%
3 71
 
0.2%
4 10
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
6 2
 
< 0.1%
5 4
 
< 0.1%
4 10
 
< 0.1%
3 71
0.2%

dst2src_fin_packets
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8585408652
Minimum0
Maximum6
Zeros5223
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:17.408813image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4592900678
Coefficient of variation (CV)0.534965878
Kurtosis8.295887335
Mean0.8585408652
Median Absolute Deviation (MAD)0
Skewness0.3415978544
Sum25442
Variance0.2109473663
MonotonicityNot monotonic
2023-06-15T12:31:17.640201image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 23590
79.6%
0 5223
 
17.6%
2 674
 
2.3%
3 102
 
0.3%
4 31
 
0.1%
5 10
 
< 0.1%
6 4
 
< 0.1%
ValueCountFrequency (%)
0 5223
 
17.6%
1 23590
79.6%
2 674
 
2.3%
3 102
 
0.3%
4 31
 
0.1%
ValueCountFrequency (%)
6 4
 
< 0.1%
5 10
 
< 0.1%
4 31
 
0.1%
3 102
 
0.3%
2 674
2.3%
Distinct24
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:17.984655image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length21
Median length4
Mean length4.508402511
Min length3

Characters and Unicode

Total characters133602
Distinct characters42
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowICMPV6
2nd rowICMPV6
3rd rowICMPV6
4th rowDHCP
5th rowDHCPV6
ValueCountFrequency (%)
http 24291
82.0%
bittorrent 2438
 
8.2%
tls 1737
 
5.9%
unknown 318
 
1.1%
icmp 309
 
1.0%
dhcpv6 305
 
1.0%
icmpv6 74
 
0.2%
http.ookla 24
 
0.1%
stun 21
 
0.1%
llmnr 20
 
0.1%
Other values (14) 97
 
0.3%
2023-06-15T12:31:18.683868image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 52891
39.6%
P 25056
18.8%
H 24639
18.4%
t 4888
 
3.7%
r 4884
 
3.7%
n 3403
 
2.5%
o 2848
 
2.1%
e 2455
 
1.8%
i 2443
 
1.8%
B 2439
 
1.8%
Other values (32) 7656
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 111401
83.4%
Lowercase Letter 21755
 
16.3%
Decimal Number 379
 
0.3%
Other Punctuation 62
 
< 0.1%
Connector Punctuation 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 52891
47.5%
P 25056
22.5%
H 24639
22.1%
B 2439
 
2.2%
L 1814
 
1.6%
S 1809
 
1.6%
C 702
 
0.6%
M 422
 
0.4%
I 403
 
0.4%
V 379
 
0.3%
Other values (10) 847
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
t 4888
22.5%
r 4884
22.5%
n 3403
15.6%
o 2848
13.1%
e 2455
11.3%
i 2443
11.2%
k 356
 
1.6%
w 323
 
1.5%
a 61
 
0.3%
l 35
 
0.2%
Other values (9) 59
 
0.3%
Decimal Number
ValueCountFrequency (%)
6 379
100.0%
Other Punctuation
ValueCountFrequency (%)
. 62
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 133156
99.7%
Common 446
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 52891
39.7%
P 25056
18.8%
H 24639
18.5%
t 4888
 
3.7%
r 4884
 
3.7%
n 3403
 
2.6%
o 2848
 
2.1%
e 2455
 
1.8%
i 2443
 
1.8%
B 2439
 
1.8%
Other values (29) 7210
 
5.4%
Common
ValueCountFrequency (%)
6 379
85.0%
. 62
 
13.9%
_ 5
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 133602
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 52891
39.6%
P 25056
18.8%
H 24639
18.4%
t 4888
 
3.7%
r 4884
 
3.7%
n 3403
 
2.5%
o 2848
 
2.1%
e 2455
 
1.8%
i 2443
 
1.8%
B 2439
 
1.8%
Other values (32) 7656
 
5.7%
Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:19.034584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length13
Median length3
Mean length3.621650807
Min length3

Characters and Unicode

Total characters107324
Distinct characters32
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowNetwork
2nd rowNetwork
3rd rowNetwork
4th rowNetwork
5th rowNetwork
ValueCountFrequency (%)
web 26012
87.8%
download 2443
 
8.2%
network 793
 
2.7%
unspecified 318
 
1.1%
advertisement 30
 
0.1%
system 13
 
< 0.1%
socialnetwork 12
 
< 0.1%
cloud 10
 
< 0.1%
media 1
 
< 0.1%
voip 1
 
< 0.1%
2023-06-15T12:31:19.801499image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 27560
25.7%
W 26012
24.2%
b 26012
24.2%
o 5715
 
5.3%
w 3248
 
3.0%
d 2802
 
2.6%
n 2791
 
2.6%
l 2465
 
2.3%
a 2456
 
2.3%
D 2443
 
2.3%
Other values (22) 5820
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 77675
72.4%
Uppercase Letter 29649
 
27.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 27560
35.5%
b 26012
33.5%
o 5715
 
7.4%
w 3248
 
4.2%
d 2802
 
3.6%
n 2791
 
3.6%
l 2465
 
3.2%
a 2456
 
3.2%
t 879
 
1.1%
r 835
 
1.1%
Other values (10) 2912
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
W 26012
87.7%
D 2443
 
8.2%
N 805
 
2.7%
U 318
 
1.1%
A 31
 
0.1%
S 25
 
0.1%
C 10
 
< 0.1%
M 1
 
< 0.1%
V 1
 
< 0.1%
I 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 107324
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 27560
25.7%
W 26012
24.2%
b 26012
24.2%
o 5715
 
5.3%
w 3248
 
3.0%
d 2802
 
2.6%
n 2791
 
2.6%
l 2465
 
2.3%
a 2456
 
2.3%
D 2443
 
2.3%
Other values (22) 5820
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107324
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 27560
25.7%
W 26012
24.2%
b 26012
24.2%
o 5715
 
5.3%
w 3248
 
3.0%
d 2802
 
2.6%
n 2791
 
2.6%
l 2465
 
2.3%
a 2456
 
2.3%
D 2443
 
2.3%
Other values (22) 5820
 
5.4%

application_is_guessed
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8228048863
Minimum0
Maximum1
Zeros5251
Zeros (%)17.7%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:20.440370image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3818401832
Coefficient of variation (CV)0.4640713607
Kurtosis0.8591988622
Mean0.8228048863
Median Absolute Deviation (MAD)0
Skewness-1.690899429
Sum24383
Variance0.1458019255
MonotonicityNot monotonic
2023-06-15T12:31:20.809139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 24383
82.3%
0 5251
 
17.7%
ValueCountFrequency (%)
0 5251
 
17.7%
1 24383
82.3%
ValueCountFrequency (%)
1 24383
82.3%
0 5251
 
17.7%

application_confidence
Real number (ℝ)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.842208274
Minimum0
Maximum6
Zeros318
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:21.137492image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.876580007
Coefficient of variation (CV)1.018657897
Kurtosis1.059984077
Mean1.842208274
Median Absolute Deviation (MAD)0
Skewness1.734503683
Sum54592
Variance3.521552522
MonotonicityNot monotonic
2023-06-15T12:31:21.482713image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 24171
81.6%
6 4920
 
16.6%
0 318
 
1.1%
4 200
 
0.7%
5 13
 
< 0.1%
3 12
 
< 0.1%
ValueCountFrequency (%)
0 318
 
1.1%
1 24171
81.6%
3 12
 
< 0.1%
4 200
 
0.7%
5 13
 
< 0.1%
ValueCountFrequency (%)
6 4920
 
16.6%
5 13
 
< 0.1%
4 200
 
0.7%
3 12
 
< 0.1%
1 24171
81.6%

requested_server_name
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29634
Missing (%)100.0%
Memory size463.0 KiB

client_fingerprint
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29634
Missing (%)100.0%
Memory size463.0 KiB
Distinct49
Distinct (%)9.4%
Missing29114
Missing (%)98.2%
Memory size463.0 KiB
2023-06-15T12:31:21.996938image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length32
Median length32
Mean length32
Min length32

Characters and Unicode

Total characters16640
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)1.7%

Sample

1st row2de81c22ea32a57162df5cb08d4a2795
2nd rowd90fa179c9daf35598ed8341272118f7
3rd row2de81c22ea32a57162df5cb08d4a2795
4th row96681175a9547081bf3d417f1a572091
5th row2de81c22ea32a57162df5cb08d4a2795
ValueCountFrequency (%)
303951d4c50efb2e991652225a6f02b1 100
19.2%
2de81c22ea32a57162df5cb08d4a2795 55
 
10.6%
7bee5c1d424b7e5f943b06983bb11422 55
 
10.6%
d199ba0af2b08e204c73d6d81a1fd260 38
 
7.3%
76cc3e2d3028143b23ec18e27dbd7ca9 24
 
4.6%
30553045c697c20ead22a41ae6655ff1 20
 
3.8%
699a80bdb17efe157c861f92c5bf5d1d 18
 
3.5%
5397c414a9ebeaff1bf18b70ca22eaa0 17
 
3.3%
8d2a028aa94425f76ced7826b1f39039 17
 
3.3%
b898351eb5e266aefd3723d466935494 16
 
3.1%
Other values (39) 160
30.8%
2023-06-15T12:31:22.909535image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1762
 
10.6%
1 1317
 
7.9%
5 1279
 
7.7%
9 1118
 
6.7%
b 1096
 
6.6%
e 1094
 
6.6%
d 1031
 
6.2%
0 1008
 
6.1%
a 954
 
5.7%
3 944
 
5.7%
Other values (6) 5037
30.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10691
64.2%
Lowercase Letter 5949
35.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1762
16.5%
1 1317
12.3%
5 1279
12.0%
9 1118
10.5%
0 1008
9.4%
3 944
8.8%
4 864
8.1%
7 842
7.9%
6 825
7.7%
8 732
6.8%
Lowercase Letter
ValueCountFrequency (%)
b 1096
18.4%
e 1094
18.4%
d 1031
17.3%
a 954
16.0%
f 896
15.1%
c 878
14.8%

Most occurring scripts

ValueCountFrequency (%)
Common 10691
64.2%
Latin 5949
35.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1762
16.5%
1 1317
12.3%
5 1279
12.0%
9 1118
10.5%
0 1008
9.4%
3 944
8.8%
4 864
8.1%
7 842
7.9%
6 825
7.7%
8 732
6.8%
Latin
ValueCountFrequency (%)
b 1096
18.4%
e 1094
18.4%
d 1031
17.3%
a 954
16.0%
f 896
15.1%
c 878
14.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16640
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1762
 
10.6%
1 1317
 
7.9%
5 1279
 
7.7%
9 1118
 
6.7%
b 1096
 
6.6%
e 1094
 
6.6%
d 1031
 
6.2%
0 1008
 
6.1%
a 954
 
5.7%
3 944
 
5.7%
Other values (6) 5037
30.3%
Distinct2
Distinct (%)28.6%
Missing29627
Missing (%)> 99.9%
Memory size463.0 KiB
2023-06-15T12:31:23.320754image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length85
Median length65
Mean length70.71428571
Min length65

Characters and Unicode

Total characters495
Distinct characters42
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMozilla/5.0 (X11; Linux x86_64; rv:43.0) Gecko/20100101 Firefox/43.0 Iceweasel/43.0.4
2nd rowMozilla/5.0 (X11; Linux x86_64; rv:43.0) Gecko/20100101 Firefox/43.0 Iceweasel/43.0.4
3rd rowMozilla/5.0 (Windows NT 6.1; rv:53.0) Gecko/20100101 Firefox/53.0
4th rowMozilla/5.0 (Windows NT 6.1; rv:53.0) Gecko/20100101 Firefox/53.0
5th rowMozilla/5.0 (Windows NT 6.1; rv:53.0) Gecko/20100101 Firefox/53.0
ValueCountFrequency (%)
mozilla/5.0 7
13.7%
gecko/20100101 7
13.7%
windows 5
9.8%
nt 5
9.8%
6.1 5
9.8%
rv:53.0 5
9.8%
firefox/53.0 5
9.8%
x11 2
 
3.9%
linux 2
 
3.9%
x86_64 2
 
3.9%
Other values (3) 6
11.8%
2023-06-15T12:31:24.005388image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 51
 
10.3%
44
 
8.9%
. 30
 
6.1%
1 30
 
6.1%
o 26
 
5.3%
/ 23
 
4.6%
i 21
 
4.2%
e 20
 
4.0%
5 17
 
3.4%
3 16
 
3.2%
Other values (32) 217
43.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 182
36.8%
Decimal Number 142
28.7%
Other Punctuation 69
 
13.9%
Space Separator 44
 
8.9%
Uppercase Letter 42
 
8.5%
Close Punctuation 7
 
1.4%
Open Punctuation 7
 
1.4%
Connector Punctuation 2
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 26
14.3%
i 21
11.5%
e 20
11.0%
l 16
 
8.8%
r 14
 
7.7%
x 11
 
6.0%
a 9
 
4.9%
c 9
 
4.9%
f 7
 
3.8%
k 7
 
3.8%
Other values (7) 42
23.1%
Uppercase Letter
ValueCountFrequency (%)
G 7
16.7%
F 7
16.7%
M 7
16.7%
W 5
11.9%
N 5
11.9%
T 5
11.9%
X 2
 
4.8%
L 2
 
4.8%
I 2
 
4.8%
Decimal Number
ValueCountFrequency (%)
0 51
35.9%
1 30
21.1%
5 17
 
12.0%
3 16
 
11.3%
4 10
 
7.0%
6 9
 
6.3%
2 7
 
4.9%
8 2
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 30
43.5%
/ 23
33.3%
; 9
 
13.0%
: 7
 
10.1%
Space Separator
ValueCountFrequency (%)
44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 271
54.7%
Latin 224
45.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 26
 
11.6%
i 21
 
9.4%
e 20
 
8.9%
l 16
 
7.1%
r 14
 
6.2%
x 11
 
4.9%
a 9
 
4.0%
c 9
 
4.0%
f 7
 
3.1%
G 7
 
3.1%
Other values (16) 84
37.5%
Common
ValueCountFrequency (%)
0 51
18.8%
44
16.2%
. 30
11.1%
1 30
11.1%
/ 23
8.5%
5 17
 
6.3%
3 16
 
5.9%
4 10
 
3.7%
6 9
 
3.3%
; 9
 
3.3%
Other values (6) 32
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 51
 
10.3%
44
 
8.9%
. 30
 
6.1%
1 30
 
6.1%
o 26
 
5.3%
/ 23
 
4.6%
i 21
 
4.2%
e 20
 
4.0%
5 17
 
3.4%
3 16
 
3.2%
Other values (32) 217
43.8%
Distinct20
Distinct (%)1.6%
Missing28403
Missing (%)95.8%
Memory size463.0 KiB
2023-06-15T12:31:24.401141image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length24
Mean length13.92363932
Min length1

Characters and Unicode

Total characters17140
Distinct characters26
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.3%

Sample

1st rowimage/gif
2nd rowapplication/javascript
3rd rowtext/javascript
4th rowtext/javascript
5th rowtext/html
ValueCountFrequency (%)
image/gif 259
21.1%
application/javascript 179
14.6%
text/html 163
13.3%
text/javascript 144
11.7%
application/json 115
9.4%
image/jpeg 101
 
8.2%
application/x-javascript 100
 
8.2%
image/png 46
 
3.8%
text/plain 33
 
2.7%
text/css 30
 
2.4%
Other values (9) 56
 
4.6%
2023-06-15T12:31:25.271357image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2144
12.5%
i 1979
11.5%
t 1782
 
10.4%
p 1487
 
8.7%
/ 1226
 
7.2%
e 931
 
5.4%
c 900
 
5.3%
g 831
 
4.8%
s 668
 
3.9%
n 661
 
3.9%
Other values (16) 4531
26.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15748
91.9%
Other Punctuation 1228
 
7.2%
Dash Punctuation 129
 
0.8%
Decimal Number 21
 
0.1%
Math Symbol 9
 
0.1%
Space Separator 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2144
13.6%
i 1979
12.6%
t 1782
11.3%
p 1487
 
9.4%
e 931
 
5.9%
c 900
 
5.7%
g 831
 
5.3%
s 668
 
4.2%
n 661
 
4.2%
j 639
 
4.1%
Other values (10) 3726
23.7%
Other Punctuation
ValueCountFrequency (%)
/ 1226
99.8%
. 2
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%
Decimal Number
ValueCountFrequency (%)
2 21
100.0%
Math Symbol
ValueCountFrequency (%)
+ 9
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15748
91.9%
Common 1392
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2144
13.6%
i 1979
12.6%
t 1782
11.3%
p 1487
 
9.4%
e 931
 
5.9%
c 900
 
5.7%
g 831
 
5.3%
s 668
 
4.2%
n 661
 
4.2%
j 639
 
4.1%
Other values (10) 3726
23.7%
Common
ValueCountFrequency (%)
/ 1226
88.1%
- 129
 
9.3%
2 21
 
1.5%
+ 9
 
0.6%
5
 
0.4%
. 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2144
12.5%
i 1979
11.5%
t 1782
 
10.4%
p 1487
 
8.7%
/ 1226
 
7.2%
e 931
 
5.4%
c 900
 
5.3%
g 831
 
4.8%
s 668
 
3.9%
n 661
 
3.9%
Other values (16) 4531
26.4%

label
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros29634
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size463.0 KiB
2023-06-15T12:31:25.632007image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-15T12:31:25.980422image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%
ValueCountFrequency (%)
0 29634
100.0%